diff --git a/example/DiffusionExample.ipynb b/example/DiffusionExample.ipynb
index 6b82b2e..b54bbe4 100644
--- a/example/DiffusionExample.ipynb
+++ b/example/DiffusionExample.ipynb
@@ -1,262 +1,262 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "following-bullet",
-   "metadata": {},
-   "source": [
-    "# Example 1. Difussion \n",
-    "\n",
-    "This example aim to set up a simple diffussion problem for demostrating the workflow of running the problem on CPU and also ploting the result"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "complete-brook",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "┌ Info: FourierFlows will use 4 threads\n",
-      "└ @ FourierFlows /home/doraho/.julia/packages/FourierFlows/DtzuG/src/FourierFlows.jl:123\n"
-     ]
-    }
-   ],
-   "source": [
-    "using MHDFlows,PyPlot\n",
-    "using LinearAlgebra: mul!, ldiv!"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "molecular-appendix",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Problem\n",
-       "  ├─────────── grid: grid (on CPU)\n",
-       "  ├───── parameters: params\n",
-       "  ├────── variables: vars\n",
-       "  ├─── state vector: sol\n",
-       "  ├─────── equation: eqn\n",
-       "  ├────────── clock: clock\n",
-       "  └──── timestepper: RK4TimeStepper"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Declare the problem on CPU\n",
-    "CPUprob  = MHDProblem(CPU();nx = 32,Lx = 2π,\n",
-    "                             ν = 1/10,\n",
-    "                            nν = 1,\n",
-    "                             η = 1/10, \n",
-    "              # Timestepper and equation options\n",
-    "                            dt = 1/50,\n",
-    "                       stepper = \"RK4\",\n",
-    "              # Float type and dealiasing\n",
-    "                             T = Float64);\n",
-    "CPUprob"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "juvenile-child",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "ProblemGenerator3D! (generic function with 1 method)"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# function of setting up the initial condition\n",
-    "function ProblemGenerator3D!(prob,L;N = prob.grid.nx)\n",
-    "\n",
-    "  xx,yy,zz = fill(0.0,N,N,N),fill(0.0,N,N,N),fill(0.0,N,N,N);\n",
-    "  \n",
-    "  for k ∈ 1:N, j ∈ 1:N, i ∈ 1:N\n",
-    "    xx[i,j,k] = prob.grid.x[i];\n",
-    "    yy[i,j,k] = prob.grid.y[j];\n",
-    "    zz[i,j,k] = prob.grid.z[k];\n",
-    "  end\n",
-    "    \n",
-    "  sl=1; sk=1; sm=1; lamlkm=sqrt(sl.^2+sk.^2+sm.^2);\n",
-    "\n",
-    "  ux = @. -0.5*(lamlkm*sl*cos(sk*xx).*sin(sl*yy).*sin(sm.*zz) +sm*sk*sin(sk*xx).*cos(sl*yy).*cos(sm.*zz));\n",
-    "  uy=  @.  0.5*(lamlkm*sk*sin(sk*xx).*cos(sl*yy).*sin(sm.*zz)-sm*sl*cos(sk*xx).*sin(sl*yy).*cos(sm.*zz));\n",
-    "  uz=  @.                 cos(sk*xx).*cos(sl*yy).*sin(sm.*zz);\n",
-    "\n",
-    "  bx = @. fill(0.0,N,N,N);\n",
-    "  by = @. fill(0.0,N,N,N);\n",
-    "  bz = @. fill(0.0,N,N,N);\n",
-    "\n",
-    "  \n",
-    "  copyto!(prob.vars.ux, ux);\n",
-    "  copyto!(prob.vars.uy, uy);\n",
-    "  copyto!(prob.vars.uz, uz);\n",
-    "  copyto!(prob.vars.bx, bx);\n",
-    "  copyto!(prob.vars.by, by);\n",
-    "  copyto!(prob.vars.bz, bz);\n",
-    "    \n",
-    "  #Update V + B Fourier Conponment\n",
-    "  uxh = prob.sol[:, :, :, prob.params.ux_ind];\n",
-    "  uyh = prob.sol[:, :, :, prob.params.uy_ind];\n",
-    "  uzh = prob.sol[:, :, :, prob.params.uz_ind];\n",
-    "    \n",
-    "  bxh = prob.sol[:, :, :, prob.params.bx_ind];\n",
-    "  byh = prob.sol[:, :, :, prob.params.by_ind];\n",
-    "  bzh = prob.sol[:, :, :, prob.params.bz_ind];\n",
-    "\n",
-    "  mul!(uxh, prob.grid.rfftplan, prob.vars.ux);   \n",
-    "  mul!(uyh, prob.grid.rfftplan, prob.vars.uy);\n",
-    "  mul!(uzh, prob.grid.rfftplan, prob.vars.uz);\n",
-    "  mul!(bxh, prob.grid.rfftplan, prob.vars.bx);\n",
-    "  mul!(byh, prob.grid.rfftplan, prob.vars.by);\n",
-    "  mul!(bzh, prob.grid.rfftplan, prob.vars.bz);\n",
-    "  \n",
-    "  prob.sol[:, :, :, prob.params.ux_ind] .= uxh;\n",
-    "  prob.sol[:, :, :, prob.params.uy_ind] .= uyh;\n",
-    "  prob.sol[:, :, :, prob.params.uz_ind] .= uzh;\n",
-    "  prob.sol[:, :, :, prob.params.bx_ind] .= bxh;\n",
-    "  prob.sol[:, :, :, prob.params.by_ind] .= byh;\n",
-    "  prob.sol[:, :, :, prob.params.bz_ind] .= bzh;\n",
-    "\n",
-    "  MHDupdatevars!(prob);\n",
-    "\n",
-    "  return nothing\n",
-    "    \n",
-    "end"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "polar-phenomenon",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "#function for monitoring the energy\n",
-    "function KEfoo(prob)\n",
-    "    vx,vy,vz = prob.vars.ux,prob.vars.uy,prob.vars.uz;\n",
-    "    return sum(vx.^2+vy.^2 + vz.^2)\n",
-    "end\n",
-    "\n",
-    "function MEfoo(prob)\n",
-    "    bx,by,bz = prob.vars.bx,prob.vars.by,prob.vars.bz;\n",
-    "    return sum(bx.^2+by.^2 + bz.^2)\n",
-    "end\n",
-    "\n",
-    "KE = Diagnostic(KEfoo, CPUprob);\n",
-    "ME = Diagnostic(MEfoo, CPUprob);"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "middle-carpet",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "# Set up the initial condition\n",
-    "ProblemGenerator3D!(CPUprob,2π);\n",
-    "\n",
-    "# Actaul computation\n",
-    "for i = 1:100\n",
-    "    MHDupdatevars!(CPUprob);\n",
-    "    stepforward!(CPUprob, [KE, ME],1)\n",
-    "end"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "missing-disabled",
-   "metadata": {},
-   "source": [
-    "## Result"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "interpreted-bunny",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "Figure(PyObject <Figure size 640x480 with 1 Axes>)"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "PyObject Text(30.0, 0.5, 'KE [code unit]')"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "t  = KE.t[2:end-1];\n",
-    "u0 = KE.data[2];\n",
-    "plot(KE.t[2:end-1],KE.data[2:end-1],\"r\",label=L\"U^2\")\n",
-    "semilogy(KE.t[2:end-1],exp.(-2*3*(t.-t[1])/10)*u0*0.8,\"k--\",label=L\"OffSet\\:predicted\\:KE\");\n",
-    "legend()\n",
-    "xlabel(\"t  [code unit]\",size=16)\n",
-    "ylabel(\"KE [code unit]\",size=16)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "developed-smooth",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Julia 4 Threads 1.5.3",
-   "language": "julia",
-   "name": "julia-4-threads-1.5"
-  },
-  "language_info": {
-   "file_extension": ".jl",
-   "mimetype": "application/julia",
-   "name": "julia",
-   "version": "1.5.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "following-bullet",
+   "metadata": {},
+   "source": [
+    "# Example 1. Difussion \n",
+    "\n",
+    "This example aim to set up a simple diffussion problem for demostrating the workflow of running the problem on CPU and also ploting the result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "complete-brook",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "┌ Info: FourierFlows will use 4 threads\n",
+      "└ @ FourierFlows /home/doraho/.julia/packages/FourierFlows/DtzuG/src/FourierFlows.jl:123\n"
+     ]
+    }
+   ],
+   "source": [
+    "using MHDFlows,PyPlot\n",
+    "using LinearAlgebra: mul!, ldiv!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "molecular-appendix",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Problem\n",
+       "  ├─────────── grid: grid (on CPU)\n",
+       "  ├───── parameters: params\n",
+       "  ├────── variables: vars\n",
+       "  ├─── state vector: sol\n",
+       "  ├─────── equation: eqn\n",
+       "  ├────────── clock: clock\n",
+       "  └──── timestepper: RK4TimeStepper"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Declare the problem on CPU\n",
+    "CPUprob  = MHDProblem(CPU();nx = 32,Lx = 2π,\n",
+    "                             ν = 1/10,\n",
+    "                            nν = 1,\n",
+    "                             η = 1/10, \n",
+    "              # Timestepper and equation options\n",
+    "                            dt = 1/50,\n",
+    "                       stepper = \"RK4\",\n",
+    "              # Float type and dealiasing\n",
+    "                             T = Float64);\n",
+    "CPUprob"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "juvenile-child",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "ProblemGenerator3D! (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# function of setting up the initial condition\n",
+    "function ProblemGenerator3D!(prob,L;N = prob.grid.nx)\n",
+    "\n",
+    "  xx,yy,zz = fill(0.0,N,N,N),fill(0.0,N,N,N),fill(0.0,N,N,N);\n",
+    "  \n",
+    "  for k ∈ 1:N, j ∈ 1:N, i ∈ 1:N\n",
+    "    xx[i,j,k] = prob.grid.x[i];\n",
+    "    yy[i,j,k] = prob.grid.y[j];\n",
+    "    zz[i,j,k] = prob.grid.z[k];\n",
+    "  end\n",
+    "    \n",
+    "  sl=1; sk=1; sm=1; lamlkm=sqrt(sl.^2+sk.^2+sm.^2);\n",
+    "\n",
+    "  ux = @. -0.5*(lamlkm*sl*cos(sk*xx).*sin(sl*yy).*sin(sm.*zz) +sm*sk*sin(sk*xx).*cos(sl*yy).*cos(sm.*zz));\n",
+    "  uy=  @.  0.5*(lamlkm*sk*sin(sk*xx).*cos(sl*yy).*sin(sm.*zz)-sm*sl*cos(sk*xx).*sin(sl*yy).*cos(sm.*zz));\n",
+    "  uz=  @.                 cos(sk*xx).*cos(sl*yy).*sin(sm.*zz);\n",
+    "\n",
+    "  bx = @. fill(0.0,N,N,N);\n",
+    "  by = @. fill(0.0,N,N,N);\n",
+    "  bz = @. fill(0.0,N,N,N);\n",
+    "\n",
+    "  \n",
+    "  copyto!(prob.vars.ux, ux);\n",
+    "  copyto!(prob.vars.uy, uy);\n",
+    "  copyto!(prob.vars.uz, uz);\n",
+    "  copyto!(prob.vars.bx, bx);\n",
+    "  copyto!(prob.vars.by, by);\n",
+    "  copyto!(prob.vars.bz, bz);\n",
+    "    \n",
+    "  #Update V + B Fourier Conponment\n",
+    "  uxh = prob.sol[:, :, :, prob.params.ux_ind];\n",
+    "  uyh = prob.sol[:, :, :, prob.params.uy_ind];\n",
+    "  uzh = prob.sol[:, :, :, prob.params.uz_ind];\n",
+    "    \n",
+    "  bxh = prob.sol[:, :, :, prob.params.bx_ind];\n",
+    "  byh = prob.sol[:, :, :, prob.params.by_ind];\n",
+    "  bzh = prob.sol[:, :, :, prob.params.bz_ind];\n",
+    "\n",
+    "  mul!(uxh, prob.grid.rfftplan, prob.vars.ux);   \n",
+    "  mul!(uyh, prob.grid.rfftplan, prob.vars.uy);\n",
+    "  mul!(uzh, prob.grid.rfftplan, prob.vars.uz);\n",
+    "  mul!(bxh, prob.grid.rfftplan, prob.vars.bx);\n",
+    "  mul!(byh, prob.grid.rfftplan, prob.vars.by);\n",
+    "  mul!(bzh, prob.grid.rfftplan, prob.vars.bz);\n",
+    "  \n",
+    "  prob.sol[:, :, :, prob.params.ux_ind] .= uxh;\n",
+    "  prob.sol[:, :, :, prob.params.uy_ind] .= uyh;\n",
+    "  prob.sol[:, :, :, prob.params.uz_ind] .= uzh;\n",
+    "  prob.sol[:, :, :, prob.params.bx_ind] .= bxh;\n",
+    "  prob.sol[:, :, :, prob.params.by_ind] .= byh;\n",
+    "  prob.sol[:, :, :, prob.params.bz_ind] .= bzh;\n",
+    "\n",
+    "  MHDupdatevars!(prob);\n",
+    "\n",
+    "  return nothing\n",
+    "    \n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "polar-phenomenon",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "#function for monitoring the energy\n",
+    "function KEfoo(prob)\n",
+    "    vx,vy,vz = prob.vars.ux,prob.vars.uy,prob.vars.uz;\n",
+    "    return sum(vx.^2+vy.^2 + vz.^2)\n",
+    "end\n",
+    "\n",
+    "function MEfoo(prob)\n",
+    "    bx,by,bz = prob.vars.bx,prob.vars.by,prob.vars.bz;\n",
+    "    return sum(bx.^2+by.^2 + bz.^2)\n",
+    "end\n",
+    "\n",
+    "KE = Diagnostic(KEfoo, CPUprob);\n",
+    "ME = Diagnostic(MEfoo, CPUprob);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "middle-carpet",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Set up the initial condition\n",
+    "ProblemGenerator3D!(CPUprob,2π);\n",
+    "\n",
+    "# Actaul computation\n",
+    "for i = 1:100\n",
+    "    MHDupdatevars!(CPUprob);\n",
+    "    stepforward!(CPUprob, [KE, ME],1)\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "missing-disabled",
+   "metadata": {},
+   "source": [
+    "## Result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "interpreted-bunny",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "Figure(PyObject <Figure size 640x480 with 1 Axes>)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "PyObject Text(30.0, 0.5, 'KE [code unit]')"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "t  = KE.t[2:end-1];\n",
+    "u0 = KE.data[2];\n",
+    "plot(KE.t[2:end-1],KE.data[2:end-1],\"r\",label=L\"U^2\")\n",
+    "semilogy(KE.t[2:end-1],exp.(-2*3*(t.-t[1])/10)*u0*0.8,\"k--\",label=L\"OffSet\\:predicted\\:KE\");\n",
+    "legend()\n",
+    "xlabel(\"t  [code unit]\",size=16)\n",
+    "ylabel(\"KE [code unit]\",size=16)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "developed-smooth",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Julia 4 Threads 1.5.3",
+   "language": "julia",
+   "name": "julia-4-threads-1.5"
+  },
+  "language_info": {
+   "file_extension": ".jl",
+   "mimetype": "application/julia",
+   "name": "julia",
+   "version": "1.5.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/example/DynamoExample.ipynb b/example/DynamoExample.ipynb
index d268bc6..29f0cd0 100644
--- a/example/DynamoExample.ipynb
+++ b/example/DynamoExample.ipynb
@@ -1,329 +1,329 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "automotive-cooperative",
-   "metadata": {},
-   "source": [
-    "# Example 3: Dyanmo with Forcing\n",
-    "This example aim to show the implmentation of force module using the MHD solver. The idea of force module is coming from [ApJ..626..853](https://ui.adsabs.harvard.edu/abs/2005ApJ...626..853M/abstract) but more simplified version in this notebook. \n",
-    "\n",
-    "The result of interation between the force and velocity field would resulting the amplification of weak magnetic field, which usually called the dynamo effect. The example is running on GPU with the resolution of $64^3$. Beaware that the result may not converge on higher resolution, which require the modification of the force module. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "median-manhattan",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "using MHDFlows,PyPlot,CUDA\n",
-    "using LinearAlgebra: mul!, ldiv!"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "latin-terminal",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "CuDevice(0): NVIDIA GeForce RTX 3080"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "device()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "violent-tokyo",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "AddForceGPU! (generic function with 1 method)"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "#force module\n",
-    "#GPU version\n",
-    "function AddForceGPU!(N, sol, t, clock, vars, params, grid)\n",
-    "    # ∂u_ih∂t + Fv_TG, here we assume F is some constant\n",
-    "    F0 = 1.37;\n",
-    "    N0 = grid.nx;\n",
-    "    l = 2;\n",
-    "    fx,fy,fz = zeros(N0,N0,N0),zeros(N0,N0,N0),zeros(N0,N0,N0);\n",
-    "    # Real Space Computation of force function\n",
-    "    for k ∈ 1:N0, j ∈ 1:N0, i ∈ 1:N0\n",
-    "        xx = l*grid.x[i];\n",
-    "        yy = l*grid.y[j];\n",
-    "        zz = l*grid.z[k];\n",
-    "        # f = F*v_TG\n",
-    "        fx[i,j,k] =   sin(xx)*cos(yy)*cos(zz);\n",
-    "        fy[i,j,k] =  -cos(xx)*sin(yy)*cos(zz);\n",
-    "        fz[i,j,k] =  0;\n",
-    "    end\n",
-    "    \n",
-    "    copyto!(vars.nonlin1, fx);\n",
-    "    copyto!(vars.nonlin2, fy);\n",
-    "    copyto!(vars.nonlin3, fz);\n",
-    "    \n",
-    "    fx = vars.nonlin1;\n",
-    "    fy = vars.nonlin2;\n",
-    "    fz = vars.nonlin3;\n",
-    "    \n",
-    "    fk_i = vars.nonlinh1;\n",
-    "    \n",
-    "    for (u_ind,f_i) ∈ zip([params.ux_ind,params.uy_ind,params.uz_ind],[fx,fy,fz])\n",
-    "        @. fk_i*=0;\n",
-    "        mul!(fk_i, grid.rfftplan, F0*f_i);  \n",
-    "        @. N[:,:,:,u_ind] += fk_i;\n",
-    "    end\n",
-    "end"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "sudden-stage",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Problem\n",
-       "  ├─────────── grid: grid (on GPU)\n",
-       "  ├───── parameters: params\n",
-       "  ├────── variables: vars\n",
-       "  ├─── state vector: sol\n",
-       "  ├─────── equation: eqn\n",
-       "  ├────────── clock: clock\n",
-       "  └──── timestepper: RK4TimeStepper"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "#parameters\n",
-    "N = 64;\n",
-    "Lx = 2π;\n",
-    "ν,η = 2e-3,5e-3;\n",
-    "dt = 1/50;\n",
-    "\n",
-    "# Testing the problem\n",
-    "GPUprob  = MHDFlows.pgen.MHDProblem(GPU();nx = N,Lx = Lx,\n",
-    "                                           ν = ν,\n",
-    "                                          nν = 1,\n",
-    "                                           η = η, \n",
-    "                             # Timestepper and equation options\n",
-    "                                          dt = dt,\n",
-    "                                     stepper = \"RK4\",\n",
-    "                                       calcF = AddForceGPU!,\n",
-    "                             # Float type and dealiasing\n",
-    "                                           T = Float64)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "useful-failing",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "ProblemGeneratorTG! (generic function with 1 method)"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "function ProblemGeneratorTG!(prob,L0,N)\n",
-    "\n",
-    "  # Output Setting  \n",
-    "  xx,yy,zz = fill(0.0,N,N,N),fill(0.0,N,N,N),fill(0.0,N,N,N);\n",
-    "  \n",
-    " l = 2*2*π/L0;    \n",
-    "  for k ∈ 1:N, j ∈ 1:N, i ∈ 1:N\n",
-    "    xx[i,j,k] = l*prob.grid.x[i];\n",
-    "    yy[i,j,k] = l*prob.grid.y[j];\n",
-    "    zz[i,j,k] = l*prob.grid.z[k];\n",
-    "  end\n",
-    "    \n",
-    "  ux = @.  sin(xx)*cos(yy)*cos(zz);\n",
-    "  uy = @.  -cos(xx)*sin(yy)*cos(zz);\n",
-    "  uz = @.  fill(0.0,N,N,N);\n",
-    "\n",
-    "  bx = @. sqrt(1e-3)*ux;\n",
-    "  by = @. sqrt(1e-3)*uy;\n",
-    "  bz = @. sqrt(1e-3)*uz;        \n",
-    "    \n",
-    "  copyto!(prob.vars.ux, ux);\n",
-    "  copyto!(prob.vars.uy, uy);\n",
-    "  copyto!(prob.vars.uz, uz);\n",
-    "  copyto!(prob.vars.bx, bx);\n",
-    "  copyto!(prob.vars.by, by);\n",
-    "  copyto!(prob.vars.bz, bz);\n",
-    "\n",
-    "  #Update V + B Fourier Conponment\n",
-    "  uxh = prob.sol[:, :, :, prob.params.ux_ind];\n",
-    "  uyh = prob.sol[:, :, :, prob.params.uy_ind];\n",
-    "  uzh = prob.sol[:, :, :, prob.params.uz_ind];\n",
-    "    \n",
-    "  bxh = prob.sol[:, :, :, prob.params.bx_ind];\n",
-    "  byh = prob.sol[:, :, :, prob.params.by_ind];\n",
-    "  bzh = prob.sol[:, :, :, prob.params.bz_ind];\n",
-    "\n",
-    "  mul!(uxh, prob.grid.rfftplan, prob.vars.ux);   \n",
-    "  mul!(uyh, prob.grid.rfftplan, prob.vars.uy);\n",
-    "  mul!(uzh, prob.grid.rfftplan, prob.vars.uz);\n",
-    "  mul!(bxh, prob.grid.rfftplan, prob.vars.bx);\n",
-    "  mul!(byh, prob.grid.rfftplan, prob.vars.by);\n",
-    "  mul!(bzh, prob.grid.rfftplan, prob.vars.bz);\n",
-    "    \n",
-    "  prob.sol[:, :, :, prob.params.ux_ind] .= uxh;\n",
-    "  prob.sol[:, :, :, prob.params.uy_ind] .= uyh;\n",
-    "  prob.sol[:, :, :, prob.params.uz_ind] .= uzh;\n",
-    "  prob.sol[:, :, :, prob.params.bx_ind] .= bxh;\n",
-    "  prob.sol[:, :, :, prob.params.by_ind] .= byh;\n",
-    "  prob.sol[:, :, :, prob.params.bz_ind] .= bzh;\n",
-    "    \n",
-    "  MHDupdatevars!(prob);\n",
-    "      \n",
-    "  return nothing\n",
-    "end"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "personalized-sweet",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#function for monitoring the energy\n",
-    "function KEfoo(prob)\n",
-    "    vx,vy,vz = prob.vars.ux,prob.vars.uy,prob.vars.uz;\n",
-    "    return sum(vx.^2+vy.^2 + vz.^2)\n",
-    "end\n",
-    "\n",
-    "function MEfoo(prob)\n",
-    "    bx,by,bz = prob.vars.bx,prob.vars.by,prob.vars.bz;\n",
-    "    return sum(bx.^2+by.^2 + bz.^2)\n",
-    "end\n",
-    "\n",
-    "KE = Diagnostic(KEfoo, GPUprob);\n",
-    "ME = Diagnostic(MEfoo, GPUprob);"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "female-mediterranean",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      " 62.875339 seconds (53.54 M CPU allocations: 26.294 GiB, 1.93% gc time) (428.00 k GPU allocations: 834.352 GiB, 0.58% gc time of which 32.96% spent allocating)\n"
-     ]
-    }
-   ],
-   "source": [
-    "#GPU for 64^3\n",
-    "L0 = 2;\n",
-    "ProblemGeneratorTG!(GPUprob,L0,N)\n",
-    "\n",
-    "CUDA.@time for i = 1:1000\n",
-    "    stepforward!(GPUprob, [KE, ME],1)\n",
-    "    MHDupdatevars!(GPUprob);\n",
-    "end"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "labeled-renaissance",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "Figure(PyObject <Figure size 640x480 with 1 Axes>)"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "PyObject Text(30.000000000000014, 0.5, 'Energy [code unit]')"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "t  = KE.t[2:end-10];\n",
-    "uu = KE.data[2:end-10];\n",
-    "bb = ME.data[2:end-10];\n",
-    "\n",
-    "semilogy(t,uu.*(GPUprob.grid.dx)^6,\"r\",label=L\"U^2\")\n",
-    "semilogy(t,bb.*(GPUprob.grid.dx)^6,\"b\",label=L\"B^2\")\n",
-    "legend()\n",
-    "xlabel(\"t  [code unit]\",size=16)\n",
-    "ylabel(\"Energy [code unit]\",size=16)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "charming-teaching",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Julia 1.5.3",
-   "language": "julia",
-   "name": "julia-1.5"
-  },
-  "language_info": {
-   "file_extension": ".jl",
-   "mimetype": "application/julia",
-   "name": "julia",
-   "version": "1.5.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "automotive-cooperative",
+   "metadata": {},
+   "source": [
+    "# Example 3: Dyanmo with Forcing\n",
+    "This example aim to show the implmentation of force module using the MHD solver. The idea of force module is coming from [ApJ..626..853](https://ui.adsabs.harvard.edu/abs/2005ApJ...626..853M/abstract) but more simplified version in this notebook. \n",
+    "\n",
+    "The result of interation between the force and velocity field would resulting the amplification of weak magnetic field, which usually called the dynamo effect. The example is running on GPU with the resolution of $64^3$. Beaware that the result may not converge on higher resolution, which require the modification of the force module. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "median-manhattan",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "using MHDFlows,PyPlot,CUDA\n",
+    "using LinearAlgebra: mul!, ldiv!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "latin-terminal",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "CuDevice(0): NVIDIA GeForce RTX 3080"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "device()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "violent-tokyo",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "AddForceGPU! (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#force module\n",
+    "#GPU version\n",
+    "function AddForceGPU!(N, sol, t, clock, vars, params, grid)\n",
+    "    # ∂u_ih∂t + Fv_TG, here we assume F is some constant\n",
+    "    F0 = 1.37;\n",
+    "    N0 = grid.nx;\n",
+    "    l = 2;\n",
+    "    fx,fy,fz = zeros(N0,N0,N0),zeros(N0,N0,N0),zeros(N0,N0,N0);\n",
+    "    # Real Space Computation of force function\n",
+    "    for k ∈ 1:N0, j ∈ 1:N0, i ∈ 1:N0\n",
+    "        xx = l*grid.x[i];\n",
+    "        yy = l*grid.y[j];\n",
+    "        zz = l*grid.z[k];\n",
+    "        # f = F*v_TG\n",
+    "        fx[i,j,k] =   sin(xx)*cos(yy)*cos(zz);\n",
+    "        fy[i,j,k] =  -cos(xx)*sin(yy)*cos(zz);\n",
+    "        fz[i,j,k] =  0;\n",
+    "    end\n",
+    "    \n",
+    "    copyto!(vars.nonlin1, fx);\n",
+    "    copyto!(vars.nonlin2, fy);\n",
+    "    copyto!(vars.nonlin3, fz);\n",
+    "    \n",
+    "    fx = vars.nonlin1;\n",
+    "    fy = vars.nonlin2;\n",
+    "    fz = vars.nonlin3;\n",
+    "    \n",
+    "    fk_i = vars.nonlinh1;\n",
+    "    \n",
+    "    for (u_ind,f_i) ∈ zip([params.ux_ind,params.uy_ind,params.uz_ind],[fx,fy,fz])\n",
+    "        @. fk_i*=0;\n",
+    "        mul!(fk_i, grid.rfftplan, F0*f_i);  \n",
+    "        @. N[:,:,:,u_ind] += fk_i;\n",
+    "    end\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "sudden-stage",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Problem\n",
+       "  ├─────────── grid: grid (on GPU)\n",
+       "  ├───── parameters: params\n",
+       "  ├────── variables: vars\n",
+       "  ├─── state vector: sol\n",
+       "  ├─────── equation: eqn\n",
+       "  ├────────── clock: clock\n",
+       "  └──── timestepper: RK4TimeStepper"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#parameters\n",
+    "N = 64;\n",
+    "Lx = 2π;\n",
+    "ν,η = 2e-3,5e-3;\n",
+    "dt = 1/50;\n",
+    "\n",
+    "# Testing the problem\n",
+    "GPUprob  = MHDFlows.pgen.MHDProblem(GPU();nx = N,Lx = Lx,\n",
+    "                                           ν = ν,\n",
+    "                                          nν = 1,\n",
+    "                                           η = η, \n",
+    "                             # Timestepper and equation options\n",
+    "                                          dt = dt,\n",
+    "                                     stepper = \"RK4\",\n",
+    "                                       calcF = AddForceGPU!,\n",
+    "                             # Float type and dealiasing\n",
+    "                                           T = Float64)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "useful-failing",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "ProblemGeneratorTG! (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "function ProblemGeneratorTG!(prob,L0,N)\n",
+    "\n",
+    "  # Output Setting  \n",
+    "  xx,yy,zz = fill(0.0,N,N,N),fill(0.0,N,N,N),fill(0.0,N,N,N);\n",
+    "  \n",
+    " l = 2*2*π/L0;    \n",
+    "  for k ∈ 1:N, j ∈ 1:N, i ∈ 1:N\n",
+    "    xx[i,j,k] = l*prob.grid.x[i];\n",
+    "    yy[i,j,k] = l*prob.grid.y[j];\n",
+    "    zz[i,j,k] = l*prob.grid.z[k];\n",
+    "  end\n",
+    "    \n",
+    "  ux = @.  sin(xx)*cos(yy)*cos(zz);\n",
+    "  uy = @.  -cos(xx)*sin(yy)*cos(zz);\n",
+    "  uz = @.  fill(0.0,N,N,N);\n",
+    "\n",
+    "  bx = @. sqrt(1e-3)*ux;\n",
+    "  by = @. sqrt(1e-3)*uy;\n",
+    "  bz = @. sqrt(1e-3)*uz;        \n",
+    "    \n",
+    "  copyto!(prob.vars.ux, ux);\n",
+    "  copyto!(prob.vars.uy, uy);\n",
+    "  copyto!(prob.vars.uz, uz);\n",
+    "  copyto!(prob.vars.bx, bx);\n",
+    "  copyto!(prob.vars.by, by);\n",
+    "  copyto!(prob.vars.bz, bz);\n",
+    "\n",
+    "  #Update V + B Fourier Conponment\n",
+    "  uxh = prob.sol[:, :, :, prob.params.ux_ind];\n",
+    "  uyh = prob.sol[:, :, :, prob.params.uy_ind];\n",
+    "  uzh = prob.sol[:, :, :, prob.params.uz_ind];\n",
+    "    \n",
+    "  bxh = prob.sol[:, :, :, prob.params.bx_ind];\n",
+    "  byh = prob.sol[:, :, :, prob.params.by_ind];\n",
+    "  bzh = prob.sol[:, :, :, prob.params.bz_ind];\n",
+    "\n",
+    "  mul!(uxh, prob.grid.rfftplan, prob.vars.ux);   \n",
+    "  mul!(uyh, prob.grid.rfftplan, prob.vars.uy);\n",
+    "  mul!(uzh, prob.grid.rfftplan, prob.vars.uz);\n",
+    "  mul!(bxh, prob.grid.rfftplan, prob.vars.bx);\n",
+    "  mul!(byh, prob.grid.rfftplan, prob.vars.by);\n",
+    "  mul!(bzh, prob.grid.rfftplan, prob.vars.bz);\n",
+    "    \n",
+    "  prob.sol[:, :, :, prob.params.ux_ind] .= uxh;\n",
+    "  prob.sol[:, :, :, prob.params.uy_ind] .= uyh;\n",
+    "  prob.sol[:, :, :, prob.params.uz_ind] .= uzh;\n",
+    "  prob.sol[:, :, :, prob.params.bx_ind] .= bxh;\n",
+    "  prob.sol[:, :, :, prob.params.by_ind] .= byh;\n",
+    "  prob.sol[:, :, :, prob.params.bz_ind] .= bzh;\n",
+    "    \n",
+    "  MHDupdatevars!(prob);\n",
+    "      \n",
+    "  return nothing\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "personalized-sweet",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#function for monitoring the energy\n",
+    "function KEfoo(prob)\n",
+    "    vx,vy,vz = prob.vars.ux,prob.vars.uy,prob.vars.uz;\n",
+    "    return sum(vx.^2+vy.^2 + vz.^2)\n",
+    "end\n",
+    "\n",
+    "function MEfoo(prob)\n",
+    "    bx,by,bz = prob.vars.bx,prob.vars.by,prob.vars.bz;\n",
+    "    return sum(bx.^2+by.^2 + bz.^2)\n",
+    "end\n",
+    "\n",
+    "KE = Diagnostic(KEfoo, GPUprob);\n",
+    "ME = Diagnostic(MEfoo, GPUprob);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "female-mediterranean",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " 62.875339 seconds (53.54 M CPU allocations: 26.294 GiB, 1.93% gc time) (428.00 k GPU allocations: 834.352 GiB, 0.58% gc time of which 32.96% spent allocating)\n"
+     ]
+    }
+   ],
+   "source": [
+    "#GPU for 64^3\n",
+    "L0 = 2;\n",
+    "ProblemGeneratorTG!(GPUprob,L0,N)\n",
+    "\n",
+    "CUDA.@time for i = 1:1000\n",
+    "    stepforward!(GPUprob, [KE, ME],1)\n",
+    "    MHDupdatevars!(GPUprob);\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "labeled-renaissance",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "Figure(PyObject <Figure size 640x480 with 1 Axes>)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "PyObject Text(30.000000000000014, 0.5, 'Energy [code unit]')"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "t  = KE.t[2:end-10];\n",
+    "uu = KE.data[2:end-10];\n",
+    "bb = ME.data[2:end-10];\n",
+    "\n",
+    "semilogy(t,uu.*(GPUprob.grid.dx)^6,\"r\",label=L\"U^2\")\n",
+    "semilogy(t,bb.*(GPUprob.grid.dx)^6,\"b\",label=L\"B^2\")\n",
+    "legend()\n",
+    "xlabel(\"t  [code unit]\",size=16)\n",
+    "ylabel(\"Energy [code unit]\",size=16)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "charming-teaching",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Julia 1.5.3",
+   "language": "julia",
+   "name": "julia-1.5"
+  },
+  "language_info": {
+   "file_extension": ".jl",
+   "mimetype": "application/julia",
+   "name": "julia",
+   "version": "1.5.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/example/GPUExample.ipynb b/example/GPUExample.ipynb
index 2c52847..9b224eb 100644
--- a/example/GPUExample.ipynb
+++ b/example/GPUExample.ipynb
@@ -1,412 +1,412 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "abandoned-amber",
-   "metadata": {},
-   "source": [
-    "# Example 2: Taylor Green Vortices on GPU"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "demonstrated-orbit",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "┌ Info: FourierFlows will use 4 threads\n",
-      "└ @ FourierFlows /home/doraho/.julia/packages/FourierFlows/DtzuG/src/FourierFlows.jl:123\n"
-     ]
-    }
-   ],
-   "source": [
-    "using MHDFlows,PyPlot,CUDA\n",
-    "using LinearAlgebra: mul!, ldiv!"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "changed-entry",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "CuDevice(0): NVIDIA GeForce RTX 3080"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "device()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "mysterious-banner",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "ProblemGeneratorTG! (generic function with 1 method)"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "function ProblemGeneratorTG!(prob,L0;N = prob.grid.nx)\n",
-    "    \n",
-    "  # Output Setting  \n",
-    "  xx,yy,zz = fill(0.0,N,N,N),fill(0.0,N,N,N),fill(0.0,N,N,N);\n",
-    "  \n",
-    "  l = 2*2*π/L0;\n",
-    "    \n",
-    "  for k ∈ 1:N, j ∈ 1:N, i ∈ 1:N\n",
-    "    xx[i,j,k] = l*prob.grid.x[i];\n",
-    "    yy[i,j,k] = l*prob.grid.y[j];\n",
-    "    zz[i,j,k] = l*prob.grid.z[k];\n",
-    "  end\n",
-    "    \n",
-    "  sl=1; sk=1; sm=1; lamlkm=sqrt(sl.^2+sk.^2+sm.^2);\n",
-    "\n",
-    "  ux = @. -0.5*(lamlkm*sl*cos(sk*xx).*sin(sl*yy).*sin(sm.*zz) + sm*sk*sin(sk*xx).*cos(sl*yy).*cos(sm.*zz));\n",
-    "  uy=  @.  0.5*(lamlkm*sk*sin(sk*xx).*cos(sl*yy).*sin(sm.*zz) - sm*sl*cos(sk*xx).*sin(sl*yy).*cos(sm.*zz));\n",
-    "  uz=  @.                 cos(sk*xx).*cos(sl*yy).*sin(sm.*zz);\n",
-    "\n",
-    "  bx = @. sin(yy)*sin(zz);\n",
-    "  by = @. sin(zz);\n",
-    "  bz = @. cos(xx)*cos(yy);\n",
-    "\n",
-    "  copyto!(prob.vars.ux, ux);\n",
-    "  copyto!(prob.vars.uy, uy);\n",
-    "  copyto!(prob.vars.uz, uz);\n",
-    "  copyto!(prob.vars.bx, bx);\n",
-    "  copyto!(prob.vars.by, by);\n",
-    "  copyto!(prob.vars.bz, bz);\n",
-    "\n",
-    "  #Update V + B Fourier Conponment\n",
-    "  uxh = prob.sol[:, :, :, prob.params.ux_ind];\n",
-    "  uyh = prob.sol[:, :, :, prob.params.uy_ind];\n",
-    "  uzh = prob.sol[:, :, :, prob.params.uz_ind];\n",
-    "    \n",
-    "  bxh = prob.sol[:, :, :, prob.params.bx_ind];\n",
-    "  byh = prob.sol[:, :, :, prob.params.by_ind];\n",
-    "  bzh = prob.sol[:, :, :, prob.params.bz_ind];\n",
-    "\n",
-    "  mul!(uxh, prob.grid.rfftplan, prob.vars.ux);   \n",
-    "  mul!(uyh, prob.grid.rfftplan, prob.vars.uy);\n",
-    "  mul!(uzh, prob.grid.rfftplan, prob.vars.uz);\n",
-    "  mul!(bxh, prob.grid.rfftplan, prob.vars.bx);\n",
-    "  mul!(byh, prob.grid.rfftplan, prob.vars.by);\n",
-    "  mul!(bzh, prob.grid.rfftplan, prob.vars.bz);\n",
-    "    \n",
-    "  prob.sol[:, :, :, prob.params.ux_ind] .= uxh;\n",
-    "  prob.sol[:, :, :, prob.params.uy_ind] .= uyh;\n",
-    "  prob.sol[:, :, :, prob.params.uz_ind] .= uzh;\n",
-    "  prob.sol[:, :, :, prob.params.bx_ind] .= bxh;\n",
-    "  prob.sol[:, :, :, prob.params.by_ind] .= byh;\n",
-    "  prob.sol[:, :, :, prob.params.bz_ind] .= bzh;\n",
-    "    \n",
-    "  MHDupdatevars!(prob);\n",
-    "      \n",
-    "  return nothing\n",
-    "end\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "obvious-newfoundland",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Problem\n",
-       "  ├─────────── grid: grid (on GPU)\n",
-       "  ├───── parameters: params\n",
-       "  ├────── variables: vars\n",
-       "  ├─── state vector: sol\n",
-       "  ├─────── equation: eqn\n",
-       "  ├────────── clock: clock\n",
-       "  └──── timestepper: RK4TimeStepper"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "#Simulation's parameters\n",
-    "N = 128;\n",
-    "Lx = 2π;\n",
-    "ν,η = 1/100,1/100;\n",
-    "dt = 1/50;\n",
-    "\n",
-    "# Testing the problem\n",
-    "# Declare the problem on GPU\n",
-    "GPUprob  = MHDProblem(GPU();nx = N,Lx = Lx,\n",
-    "                             ν = ν,\n",
-    "                            nν = 1,\n",
-    "                             η = η, \n",
-    "              # Timestepper and equation options\n",
-    "                            dt = 1/50,\n",
-    "                       stepper = \"RK4\",\n",
-    "              # Float type and dealiasing\n",
-    "                             T = Float64);\n",
-    "GPUprob"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "compatible-constraint",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "#function for monitoring the energy\n",
-    "function KEfoo(prob)\n",
-    "    vx,vy,vz = prob.vars.ux,prob.vars.uy,prob.vars.uz;\n",
-    "    return sum(vx.^2+vy.^2 + vz.^2)\n",
-    "end\n",
-    "\n",
-    "function MEfoo(prob)\n",
-    "    bx,by,bz = prob.vars.bx,prob.vars.by,prob.vars.bz;\n",
-    "    return sum(bx.^2+by.^2 + bz.^2)\n",
-    "end\n",
-    "\n",
-    "KE = Diagnostic(KEfoo, GPUprob);\n",
-    "ME = Diagnostic(MEfoo, GPUprob);"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "breathing-pixel",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Set up the initial condition\n",
-    "ProblemGeneratorTG!(GPUprob,2π);\n",
-    "\n",
-    "# Actaul computation\n",
-    "for i = 1:200\n",
-    "    MHDupdatevars!(GPUprob);\n",
-    "    stepforward!(GPUprob, [KE, ME],1)\n",
-    "end"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "sexual-actress",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "Figure(PyObject <Figure size 640x480 with 1 Axes>)"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "PyObject Text(30.0, 0.5, 'Energy [code unit]')"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "t  = KE.t[2:end-1];\n",
-    "uu = KE.data[2:end-1];\n",
-    "bb = ME.data[2:end-1];\n",
-    "\n",
-    "semilogy(t,uu,\"r\",label=L\"U^2\")\n",
-    "semilogy(t,bb,\"b\",label=L\"B^2\")\n",
-    "legend()\n",
-    "xlabel(\"t  [code unit]\",size=16)\n",
-    "ylabel(\"Energy [code unit]\",size=16)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "scenic-affairs",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Effective GPU memory usage: 100.00% (10.000 GiB/10.000 GiB)\n",
-      "CUDA allocator usage: 9.063 GiB\n",
-      "binned usage: 9.063 GiB (1.766 GiB allocated, 7.297 GiB cached)\n",
-      "Effective GPU memory usage: 29.47% (2.947 GiB/10.000 GiB)\n",
-      "CUDA allocator usage: 1.766 GiB\n",
-      "binned usage: 1.766 GiB (1.391 GiB allocated, 384.000 MiB cached)\n"
-     ]
-    }
-   ],
-   "source": [
-    "CUDA.memory_status()\n",
-    "CUDA.reclaim()\n",
-    "GC.gc(true)\n",
-    "CUDA.memory_status()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "id": "fatal-parts",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "Figure(PyObject <Figure size 640x480 with 1 Axes>)"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "PyObject <matplotlib.image.AxesImage object at 0x7f7962e262e8>"
-      ]
-     },
-     "execution_count": 9,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "imshow(Array(@view GPUprob.vars.ux[:,:,20]))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "destroyed-reply",
-   "metadata": {},
-   "source": [
-    "# Comparsion between CPU and GPU runtime"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "id": "mediterranean-measure",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Effective GPU memory usage: 25.72% (2.572 GiB/10.000 GiB)\n",
-      "CUDA allocator usage: 1.391 GiB\n",
-      "binned usage: 1.391 GiB (1.391 GiB allocated, 0 bytes cached)\n",
-      "  2.944566 seconds (317.08 k CPU allocations: 20.177 MiB, 3.59% gc time) (3.78 k GPU allocations: 59.282 GiB, 6.52% gc time of which 36.82% spent allocating)\n"
-     ]
-    }
-   ],
-   "source": [
-    "CUDA.reclaim()\n",
-    "GC.gc(true)\n",
-    "CUDA.memory_status()\n",
-    "\n",
-    "#GPU on 128^3\n",
-    "GPUprob  = MHDProblem(GPU();nx = N,Lx = Lx,\n",
-    "                             ν = ν,\n",
-    "                            nν = 1,\n",
-    "                             η = η, \n",
-    "              # Timestepper and equation options\n",
-    "                            dt = 1/50,\n",
-    "                       stepper = \"RK4\",\n",
-    "              # Float type and dealiasing\n",
-    "                             T = Float64);\n",
-    "\n",
-    "ProblemGeneratorTG!(GPUprob,2π);\n",
-    "# Actaul computation\n",
-    "@CUDA.time for i = 1:10\n",
-    "    MHDupdatevars!(GPUprob);\n",
-    "    stepforward!(GPUprob,1)\n",
-    "end"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "id": "stock-matter",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      " 17.822334 seconds (9.59 M allocations: 5.210 GiB, 0.57% gc time)\n"
-     ]
-    }
-   ],
-   "source": [
-    "#CPU on 128^3\n",
-    "CPUprob  = MHDProblem(CPU();nx = N,Lx = Lx,\n",
-    "                             ν = ν,\n",
-    "                            nν = 1,\n",
-    "                             η = η, \n",
-    "              # Timestepper and equation options\n",
-    "                            dt = 1/50,\n",
-    "                       stepper = \"RK4\",\n",
-    "              # Float type and dealiasing\n",
-    "                             T = Float32);\n",
-    "\n",
-    "ProblemGeneratorTG!(CPUprob,2π);\n",
-    "# Actaul computation  \n",
-    "@time for i = 1:10\n",
-    "    MHDupdatevars!(CPUprob);\n",
-    "    stepforward!(CPUprob, [KE, ME],1)\n",
-    "end"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Julia 4 Threads 1.5.3",
-   "language": "julia",
-   "name": "julia-4-threads-1.5"
-  },
-  "language_info": {
-   "file_extension": ".jl",
-   "mimetype": "application/julia",
-   "name": "julia",
-   "version": "1.5.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "abandoned-amber",
+   "metadata": {},
+   "source": [
+    "# Example 2: Taylor Green Vortices on GPU"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "demonstrated-orbit",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "┌ Info: FourierFlows will use 4 threads\n",
+      "└ @ FourierFlows /home/doraho/.julia/packages/FourierFlows/DtzuG/src/FourierFlows.jl:123\n"
+     ]
+    }
+   ],
+   "source": [
+    "using MHDFlows,PyPlot,CUDA\n",
+    "using LinearAlgebra: mul!, ldiv!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "changed-entry",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "CuDevice(0): NVIDIA GeForce RTX 3080"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "device()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "mysterious-banner",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "ProblemGeneratorTG! (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "function ProblemGeneratorTG!(prob,L0;N = prob.grid.nx)\n",
+    "    \n",
+    "  # Output Setting  \n",
+    "  xx,yy,zz = fill(0.0,N,N,N),fill(0.0,N,N,N),fill(0.0,N,N,N);\n",
+    "  \n",
+    "  l = 2*2*π/L0;\n",
+    "    \n",
+    "  for k ∈ 1:N, j ∈ 1:N, i ∈ 1:N\n",
+    "    xx[i,j,k] = l*prob.grid.x[i];\n",
+    "    yy[i,j,k] = l*prob.grid.y[j];\n",
+    "    zz[i,j,k] = l*prob.grid.z[k];\n",
+    "  end\n",
+    "    \n",
+    "  sl=1; sk=1; sm=1; lamlkm=sqrt(sl.^2+sk.^2+sm.^2);\n",
+    "\n",
+    "  ux = @. -0.5*(lamlkm*sl*cos(sk*xx).*sin(sl*yy).*sin(sm.*zz) + sm*sk*sin(sk*xx).*cos(sl*yy).*cos(sm.*zz));\n",
+    "  uy=  @.  0.5*(lamlkm*sk*sin(sk*xx).*cos(sl*yy).*sin(sm.*zz) - sm*sl*cos(sk*xx).*sin(sl*yy).*cos(sm.*zz));\n",
+    "  uz=  @.                 cos(sk*xx).*cos(sl*yy).*sin(sm.*zz);\n",
+    "\n",
+    "  bx = @. sin(yy)*sin(zz);\n",
+    "  by = @. sin(zz);\n",
+    "  bz = @. cos(xx)*cos(yy);\n",
+    "\n",
+    "  copyto!(prob.vars.ux, ux);\n",
+    "  copyto!(prob.vars.uy, uy);\n",
+    "  copyto!(prob.vars.uz, uz);\n",
+    "  copyto!(prob.vars.bx, bx);\n",
+    "  copyto!(prob.vars.by, by);\n",
+    "  copyto!(prob.vars.bz, bz);\n",
+    "\n",
+    "  #Update V + B Fourier Conponment\n",
+    "  uxh = prob.sol[:, :, :, prob.params.ux_ind];\n",
+    "  uyh = prob.sol[:, :, :, prob.params.uy_ind];\n",
+    "  uzh = prob.sol[:, :, :, prob.params.uz_ind];\n",
+    "    \n",
+    "  bxh = prob.sol[:, :, :, prob.params.bx_ind];\n",
+    "  byh = prob.sol[:, :, :, prob.params.by_ind];\n",
+    "  bzh = prob.sol[:, :, :, prob.params.bz_ind];\n",
+    "\n",
+    "  mul!(uxh, prob.grid.rfftplan, prob.vars.ux);   \n",
+    "  mul!(uyh, prob.grid.rfftplan, prob.vars.uy);\n",
+    "  mul!(uzh, prob.grid.rfftplan, prob.vars.uz);\n",
+    "  mul!(bxh, prob.grid.rfftplan, prob.vars.bx);\n",
+    "  mul!(byh, prob.grid.rfftplan, prob.vars.by);\n",
+    "  mul!(bzh, prob.grid.rfftplan, prob.vars.bz);\n",
+    "    \n",
+    "  prob.sol[:, :, :, prob.params.ux_ind] .= uxh;\n",
+    "  prob.sol[:, :, :, prob.params.uy_ind] .= uyh;\n",
+    "  prob.sol[:, :, :, prob.params.uz_ind] .= uzh;\n",
+    "  prob.sol[:, :, :, prob.params.bx_ind] .= bxh;\n",
+    "  prob.sol[:, :, :, prob.params.by_ind] .= byh;\n",
+    "  prob.sol[:, :, :, prob.params.bz_ind] .= bzh;\n",
+    "    \n",
+    "  MHDupdatevars!(prob);\n",
+    "      \n",
+    "  return nothing\n",
+    "end\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "obvious-newfoundland",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Problem\n",
+       "  ├─────────── grid: grid (on GPU)\n",
+       "  ├───── parameters: params\n",
+       "  ├────── variables: vars\n",
+       "  ├─── state vector: sol\n",
+       "  ├─────── equation: eqn\n",
+       "  ├────────── clock: clock\n",
+       "  └──── timestepper: RK4TimeStepper"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Simulation's parameters\n",
+    "N = 128;\n",
+    "Lx = 2π;\n",
+    "ν,η = 1/100,1/100;\n",
+    "dt = 1/50;\n",
+    "\n",
+    "# Testing the problem\n",
+    "# Declare the problem on GPU\n",
+    "GPUprob  = MHDProblem(GPU();nx = N,Lx = Lx,\n",
+    "                             ν = ν,\n",
+    "                            nν = 1,\n",
+    "                             η = η, \n",
+    "              # Timestepper and equation options\n",
+    "                            dt = 1/50,\n",
+    "                       stepper = \"RK4\",\n",
+    "              # Float type and dealiasing\n",
+    "                             T = Float64);\n",
+    "GPUprob"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "compatible-constraint",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "#function for monitoring the energy\n",
+    "function KEfoo(prob)\n",
+    "    vx,vy,vz = prob.vars.ux,prob.vars.uy,prob.vars.uz;\n",
+    "    return sum(vx.^2+vy.^2 + vz.^2)\n",
+    "end\n",
+    "\n",
+    "function MEfoo(prob)\n",
+    "    bx,by,bz = prob.vars.bx,prob.vars.by,prob.vars.bz;\n",
+    "    return sum(bx.^2+by.^2 + bz.^2)\n",
+    "end\n",
+    "\n",
+    "KE = Diagnostic(KEfoo, GPUprob);\n",
+    "ME = Diagnostic(MEfoo, GPUprob);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "breathing-pixel",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Set up the initial condition\n",
+    "ProblemGeneratorTG!(GPUprob,2π);\n",
+    "\n",
+    "# Actaul computation\n",
+    "for i = 1:200\n",
+    "    MHDupdatevars!(GPUprob);\n",
+    "    stepforward!(GPUprob, [KE, ME],1)\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "sexual-actress",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "Figure(PyObject <Figure size 640x480 with 1 Axes>)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "PyObject Text(30.0, 0.5, 'Energy [code unit]')"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "t  = KE.t[2:end-1];\n",
+    "uu = KE.data[2:end-1];\n",
+    "bb = ME.data[2:end-1];\n",
+    "\n",
+    "semilogy(t,uu,\"r\",label=L\"U^2\")\n",
+    "semilogy(t,bb,\"b\",label=L\"B^2\")\n",
+    "legend()\n",
+    "xlabel(\"t  [code unit]\",size=16)\n",
+    "ylabel(\"Energy [code unit]\",size=16)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "scenic-affairs",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Effective GPU memory usage: 100.00% (10.000 GiB/10.000 GiB)\n",
+      "CUDA allocator usage: 9.063 GiB\n",
+      "binned usage: 9.063 GiB (1.766 GiB allocated, 7.297 GiB cached)\n",
+      "Effective GPU memory usage: 29.47% (2.947 GiB/10.000 GiB)\n",
+      "CUDA allocator usage: 1.766 GiB\n",
+      "binned usage: 1.766 GiB (1.391 GiB allocated, 384.000 MiB cached)\n"
+     ]
+    }
+   ],
+   "source": [
+    "CUDA.memory_status()\n",
+    "CUDA.reclaim()\n",
+    "GC.gc(true)\n",
+    "CUDA.memory_status()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "fatal-parts",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "Figure(PyObject <Figure size 640x480 with 1 Axes>)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "PyObject <matplotlib.image.AxesImage object at 0x7f7962e262e8>"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "imshow(Array(@view GPUprob.vars.ux[:,:,20]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "destroyed-reply",
+   "metadata": {},
+   "source": [
+    "# Comparsion between CPU and GPU runtime"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "mediterranean-measure",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Effective GPU memory usage: 25.72% (2.572 GiB/10.000 GiB)\n",
+      "CUDA allocator usage: 1.391 GiB\n",
+      "binned usage: 1.391 GiB (1.391 GiB allocated, 0 bytes cached)\n",
+      "  2.944566 seconds (317.08 k CPU allocations: 20.177 MiB, 3.59% gc time) (3.78 k GPU allocations: 59.282 GiB, 6.52% gc time of which 36.82% spent allocating)\n"
+     ]
+    }
+   ],
+   "source": [
+    "CUDA.reclaim()\n",
+    "GC.gc(true)\n",
+    "CUDA.memory_status()\n",
+    "\n",
+    "#GPU on 128^3\n",
+    "GPUprob  = MHDProblem(GPU();nx = N,Lx = Lx,\n",
+    "                             ν = ν,\n",
+    "                            nν = 1,\n",
+    "                             η = η, \n",
+    "              # Timestepper and equation options\n",
+    "                            dt = 1/50,\n",
+    "                       stepper = \"RK4\",\n",
+    "              # Float type and dealiasing\n",
+    "                             T = Float64);\n",
+    "\n",
+    "ProblemGeneratorTG!(GPUprob,2π);\n",
+    "# Actaul computation\n",
+    "@CUDA.time for i = 1:10\n",
+    "    MHDupdatevars!(GPUprob);\n",
+    "    stepforward!(GPUprob,1)\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "stock-matter",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " 17.822334 seconds (9.59 M allocations: 5.210 GiB, 0.57% gc time)\n"
+     ]
+    }
+   ],
+   "source": [
+    "#CPU on 128^3\n",
+    "CPUprob  = MHDProblem(CPU();nx = N,Lx = Lx,\n",
+    "                             ν = ν,\n",
+    "                            nν = 1,\n",
+    "                             η = η, \n",
+    "              # Timestepper and equation options\n",
+    "                            dt = 1/50,\n",
+    "                       stepper = \"RK4\",\n",
+    "              # Float type and dealiasing\n",
+    "                             T = Float32);\n",
+    "\n",
+    "ProblemGeneratorTG!(CPUprob,2π);\n",
+    "# Actaul computation  \n",
+    "@time for i = 1:10\n",
+    "    MHDupdatevars!(CPUprob);\n",
+    "    stepforward!(CPUprob, [KE, ME],1)\n",
+    "end"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Julia 4 Threads 1.5.3",
+   "language": "julia",
+   "name": "julia-4-threads-1.5"
+  },
+  "language_info": {
+   "file_extension": ".jl",
+   "mimetype": "application/julia",
+   "name": "julia",
+   "version": "1.5.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/example/HD_InstabilityExample.ipynb b/example/HD_InstabilityExample.ipynb
new file mode 100644
index 0000000..0db14b9
--- /dev/null
+++ b/example/HD_InstabilityExample.ipynb
@@ -0,0 +1,684 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "chubby-color",
+   "metadata": {},
+   "source": [
+    "# Example for HD Module \n",
+    "This example aim to show the workflow of HD Solver though the analytic example from [Antuono (2020)](https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/triperiodic-fully-threedimensional-analytic-solutions-for-the-navierstokes-equations/0444128148C6D5217F6F78B8C9BB0219) and also explore if MHDflows could resolve the turbulence properties."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "digital-enterprise",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "┌ Info: FourierFlows will use 4 threads\n",
+      "└ @ FourierFlows /home/doraho/.julia/packages/FourierFlows/DtzuG/src/FourierFlows.jl:123\n"
+     ]
+    }
+   ],
+   "source": [
+    "using MHDFlows\n",
+    "using PyCall,PyPlot\n",
+    "using FFTW,CUDA,Statistics\n",
+    "using LinearAlgebra: mul!, ldiv!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "julian-framing",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CuDevice(1)"
+     ]
+    }
+   ],
+   "source": [
+    "device!(1)\n",
+    "print(device())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "fatal-teens",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "ProblemGeneratorTG! (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "function ProblemGeneratorTG!(prob,L0,U0;N = prob.grid.nx)\n",
+    "  R     = 0;\n",
+    "\n",
+    "  # Output Setting  \n",
+    "  kx,ky,kz = fill(0.0,N,N,N),fill(0.0,N,N,N),fill(0.0,N,N,N);\n",
+    "  \n",
+    "  l = 2*π/L0;\n",
+    "    \n",
+    "  for k ∈ 1:N, j ∈ 1:N, i ∈ 1:N\n",
+    "    kx[i,j,k] = l*prob.grid.x[i];\n",
+    "    ky[i,j,k] = l*prob.grid.y[j];\n",
+    "    kz[i,j,k] = l*prob.grid.z[k];\n",
+    "  end\n",
+    "    \n",
+    "  pfactor =  4/3*sqrt(2/3);\n",
+    "    \n",
+    "  θ1 = asin(-(√(3)+R)/2/√(1+R^2));\n",
+    "  Φ1 = asin((√(3)-R)/2/√(1+R^2));\n",
+    "  ϕ1 = asin(1/(1+R^2));\n",
+    "    \n",
+    "  ux = @. (sin(kx+θ1)*cos(ky+Φ1)*sin(kz+ϕ1) - cos(kz+θ1)*sin(kx+Φ1)*sin(ky+ϕ1));\n",
+    "  \n",
+    "  uy = @. (sin(ky+θ1)*cos(kz+Φ1)*sin(kx+ϕ1) - cos(kx+θ1)*sin(ky+Φ1)*sin(kz+ϕ1));\n",
+    "  \n",
+    "  uz = @. (sin(kz+θ1)*cos(kx+Φ1)*sin(ky+ϕ1) - cos(ky+θ1)*sin(kz+Φ1)*sin(kx+ϕ1));\n",
+    "\n",
+    "\n",
+    "  copyto!(prob.vars.ux, U0*pfactor*ux);\n",
+    "  copyto!(prob.vars.uy, U0*pfactor*uy);\n",
+    "  copyto!(prob.vars.uz, U0*pfactor*uz);\n",
+    "\n",
+    "  #Update V  Fourier Conponment\n",
+    "  uxh = prob.sol[:, :, :, prob.params.ux_ind];\n",
+    "  uyh = prob.sol[:, :, :, prob.params.uy_ind];\n",
+    "  uzh = prob.sol[:, :, :, prob.params.uz_ind];\n",
+    "\n",
+    "  mul!(uxh, prob.grid.rfftplan, prob.vars.ux);   \n",
+    "  mul!(uyh, prob.grid.rfftplan, prob.vars.uy);\n",
+    "  mul!(uzh, prob.grid.rfftplan, prob.vars.uz);\n",
+    "    \n",
+    "  prob.sol[:, :, :, prob.params.ux_ind] .= uxh;\n",
+    "  prob.sol[:, :, :, prob.params.uy_ind] .= uyh;\n",
+    "  prob.sol[:, :, :, prob.params.uz_ind] .= uzh;\n",
+    "    \n",
+    "  HDupdatevars!(prob);\n",
+    "      \n",
+    "  return nothing\n",
+    "end\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "banned-shell",
+   "metadata": {},
+   "source": [
+    "# Re = 50 Case"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "artistic-science",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Problem\n",
+       "  ├─────────── grid: grid (on GPU)\n",
+       "  ├───── parameters: params\n",
+       "  ├────── variables: vars\n",
+       "  ├─── state vector: sol\n",
+       "  ├─────── equation: eqn\n",
+       "  ├────────── clock: clock\n",
+       "  └──── timestepper: RK4TimeStepper"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Simulation's parameters\n",
+    "N = 32;\n",
+    "Lx = 2π;\n",
+    "Re = 50;\n",
+    "U0 = 6.5\n",
+    "ν = 2*π*U0/Re;\n",
+    "dt = 1/500;\n",
+    "\n",
+    "# Testing the problem\n",
+    "# Declare the problem on GPU\n",
+    "GPUprob  = HDProblem(GPU();nx = N,Lx = Lx,\n",
+    "                             ν = ν,\n",
+    "                            nν = 1,\n",
+    "              # Timestepper and equation options\n",
+    "                            dt = dt,\n",
+    "                       stepper = \"RK4\",\n",
+    "              # Float type and dealiasing\n",
+    "                             T = Float32);\n",
+    "GPUprob"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "coordinated-bubble",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#function for monitoring the energy\n",
+    "function KEfoo(prob)\n",
+    "    vx,vy,vz = prob.vars.ux,prob.vars.uy,prob.vars.uz;\n",
+    "    return sum(vx.^2+vy.^2 + vz.^2)\n",
+    "end\n",
+    "\n",
+    "KE = Diagnostic(KEfoo, GPUprob,freq=10);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "adverse-michigan",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Effective GPU memory usage: 13.50% (1.080 GiB/8.000 GiB)\n",
+      "CUDA allocator usage: 11.376 MiB\n",
+      "binned usage: 11.376 MiB (10.125 MiB allocated, 1.250 MiB cached)\n",
+      "Effective GPU memory usage: 13.50% (1.080 GiB/8.000 GiB)\n",
+      "CUDA allocator usage: 10.125 MiB\n",
+      "binned usage: 10.125 MiB (9.750 MiB allocated, 384.000 KiB cached)\n"
+     ]
+    }
+   ],
+   "source": [
+    "CUDA.memory_status()\n",
+    "CUDA.reclaim()\n",
+    "GC.gc(true)\n",
+    "CUDA.memory_status()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "smart-optimum",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Set up the initial condition\n",
+    "ProblemGeneratorTG!(GPUprob,2π,U0);\n",
+    "\n",
+    "t0 = 1\n",
+    "# Actaul computation\n",
+    "for i = 1:div(t0,dt)\n",
+    "    HDupdatevars!(GPUprob);\n",
+    "    stepforward!(GPUprob,KE,1)\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "unexpected-waterproof",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "Figure(PyObject <Figure size 640x480 with 1 Axes>)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "(0.0, 1.0)"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Plotting of the change of KE\n",
+    "t  = KE.t[1:end-5];\n",
+    "uu = KE.data[1:end-5];\n",
+    "uu[1] = U0^2*N^3;\n",
+    "nn = length(t)\n",
+    "k² = 1\n",
+    "v0 = 2*π*U0/Re;\n",
+    "plt.plot(t[1:nn],uu[1:nn]/uu[1]/2,\"r\",label=L\"(U/U_0)^2\")\n",
+    "plt.plot(t[1:1:nn],1/2*exp.(-6*v0*k²*(t[1:1:nn].-t[1])),\"kx\",label=L\"e^{-6vk^2t}\")\n",
+    "plt.title(L\"Re =\"*string(round(Re)),fontsize=15)\n",
+    "plt.legend(fontsize=15)\n",
+    "plt.xlabel(\"t  [code unit]\",size=16)\n",
+    "plt.ylabel(\"Energy [code unit]\",size=16)\n",
+    "plt.grid()\n",
+    "plt.ylim(0,0.55)\n",
+    "plt.xlim(0,1.0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "possible-daughter",
+   "metadata": {},
+   "source": [
+    "# Re = 1000 Case"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "authentic-fishing",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Problem\n",
+       "  ├─────────── grid: grid (on GPU)\n",
+       "  ├───── parameters: params\n",
+       "  ├────── variables: vars\n",
+       "  ├─── state vector: sol\n",
+       "  ├─────── equation: eqn\n",
+       "  ├────────── clock: clock\n",
+       "  └──── timestepper: RK4TimeStepper"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Simulation's parameters\n",
+    "N = 32;\n",
+    "Lx = 2π;\n",
+    "Re = 1000;\n",
+    "U0 = 6.5\n",
+    "ν = 2*π*U0/Re;\n",
+    "dt = 1/500;\n",
+    "\n",
+    "# Testing the problem\n",
+    "# Declare the problem on GPU\n",
+    "GPUprob  = HDProblem(GPU();nx = N,Lx = Lx,\n",
+    "                             ν = ν,\n",
+    "                            nν = 1,\n",
+    "              # Timestepper and equation options\n",
+    "                            dt = dt,\n",
+    "                       stepper = \"RK4\",\n",
+    "              # Float type and dealiasing\n",
+    "                             T = Float32);\n",
+    "GPUprob"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "synthetic-terminology",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Set up the initial condition\n",
+    "ProblemGeneratorTG!(GPUprob,2π,U0);\n",
+    "KE = Diagnostic(KEfoo, GPUprob,freq=10);\n",
+    "\n",
+    "t0 = 9\n",
+    "# Actaul computation\n",
+    "for i = 1:div(t0,dt)\n",
+    "    HDupdatevars!(GPUprob);\n",
+    "    stepforward!(GPUprob,KE,1)\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "oriented-genealogy",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "Figure(PyObject <Figure size 640x480 with 1 Axes>)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "(0.0, 9.0)"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Plotting of the change of KE\n",
+    "t  = KE.t[1:end-2];\n",
+    "uu = KE.data[1:end-2];\n",
+    "uu[1] = U0^2*N^3;\n",
+    "nn = length(t)-1\n",
+    "k² = 1\n",
+    "v0 = 2*π*U0/Re;\n",
+    "plt.plot(t[1:nn],uu[1:nn]/uu[1]/2,\"r\",label=L\"(U/U_0)^2\")\n",
+    "plt.plot(t[1:30:nn],1/2*exp.(-6*v0*k²*(t[1:30:nn].-t[1])),\"kx\",label=L\" e^{-6vk^2t}\")\n",
+    "plt.title(L\"Re =\"*string(round(Re)),fontsize=15)\n",
+    "plt.legend(fontsize=15)\n",
+    "plt.xlabel(\"t  [code unit]\",size=16)\n",
+    "plt.ylabel(\"Energy [code unit]\",size=16)\n",
+    "plt.grid()\n",
+    "plt.ylim(0,0.55)\n",
+    "plt.xlim(0,9.0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "prescription-syntax",
+   "metadata": {},
+   "source": [
+    "### Diference between MHDFlow and  Antuono (2020).\n",
+    "Instability doesn't arises from our simulation at Re = 1000, but we are always further check if instability happens in higher Re case with higher resolution"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "charged-fellowship",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Problem\n",
+       "  ├─────────── grid: grid (on GPU)\n",
+       "  ├───── parameters: params\n",
+       "  ├────── variables: vars\n",
+       "  ├─── state vector: sol\n",
+       "  ├─────── equation: eqn\n",
+       "  ├────────── clock: clock\n",
+       "  └──── timestepper: RK4TimeStepper"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Simulation's parameters\n",
+    "N = 256;\n",
+    "Lx = 2π;\n",
+    "Re = 5000;\n",
+    "U0 = 6.5\n",
+    "ν  = 2*π*U0/Re;\n",
+    "dt = 1/500;\n",
+    "\n",
+    "# Testing the problem\n",
+    "# Declare the problem on GPU\n",
+    "GPUprob  = HDProblem(GPU();nx = N,Lx = Lx,\n",
+    "                             ν = ν,\n",
+    "                            nν = 1,\n",
+    "              # Timestepper and equation options\n",
+    "                            dt = dt,\n",
+    "                       stepper = \"RK4\",\n",
+    "              # Float type and dealiasing\n",
+    "                             T = Float32);\n",
+    "GPUprob"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "responsible-ground",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Effective GPU memory usage: 65.01% (5.201 GiB/8.000 GiB)\n",
+      "CUDA allocator usage: 4.101 GiB\n",
+      "binned usage: 4.101 GiB (4.101 GiB allocated, 0 bytes cached)\n",
+      "Effective GPU memory usage: 65.01% (5.201 GiB/8.000 GiB)\n",
+      "CUDA allocator usage: 4.101 GiB\n",
+      "binned usage: 4.101 GiB (4.101 GiB allocated, 0 bytes cached)\n"
+     ]
+    }
+   ],
+   "source": [
+    "CUDA.memory_status()\n",
+    "CUDA.reclaim()\n",
+    "GC.gc(true)\n",
+    "CUDA.memory_status()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "italian-corner",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Set up the initial condition\n",
+    "ProblemGeneratorTG!(GPUprob,2π,U0);\n",
+    "KE = Diagnostic(KEfoo, GPUprob,freq=10);\n",
+    "\n",
+    "t0 = 8\n",
+    "# Actaul computation\n",
+    "for i = 1:div(t0,dt)\n",
+    "    HDupdatevars!(GPUprob);\n",
+    "    stepforward!(GPUprob,KE,1)\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "white-linux",
+   "metadata": {},
+   "source": [
+    "From Re~5000 case, we observe the instability behavior in our solver at t ~ 6.5"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "straight-administration",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "Figure(PyObject <Figure size 640x480 with 1 Axes>)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "(0.0, 8.0)"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Plotting of the change of KE\n",
+    "t  = KE.t[1:end-2];\n",
+    "uu = KE.data[1:end-2];\n",
+    "uu[1] = U0^2*N^3;\n",
+    "nn = length(t)-5\n",
+    "k² = 1\n",
+    "v0 = 2*π*U0/Re;\n",
+    "plt.plot(t[1:nn],uu[1:nn]/uu[1]/2,\"r\",label=L\"U^2\")\n",
+    "plt.plot(t[1:30:nn],1/2*exp.(-6*v0*k²*(t[1:30:nn].-t[1])),\"kx\",label=L\"U_0^2 e^{-6vk^2t}\")\n",
+    "plt.title(L\"Re =\"*string(round(Re)),fontsize=15)\n",
+    "plt.legend(fontsize=15)\n",
+    "plt.xlabel(\"t  [code unit]\",size=16)\n",
+    "plt.ylabel(\"Energy [code unit]\",size=16)\n",
+    "plt.grid()\n",
+    "plt.ylim(0,0.55)\n",
+    "plt.xlim(0,8.0)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "trained-conservation",
+   "metadata": {},
+   "source": [
+    "To see if it is an instability driven turbulence, we check its spectrum and strcuture in below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "spoken-reset",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Spectrun Function\n",
+    "#Athor: KH Yuen \n",
+    "function spectrallines3D(A::Array)\n",
+    " nx,ny,nz=size(A);\n",
+    " nl=round(Int,sqrt(nx^2+ny^2+nz^2));\n",
+    " kn=zeros(nl);\n",
+    " kl=zeros(nl);\n",
+    " Ax2=fftshift((abs.(fft(A))).^2.0);\n",
+    " for i in 1:nx, j in 1:ny, k in 1:nz\n",
+    "  idx=i-div(nx,2);\n",
+    "  jdx=j-div(ny,2);\n",
+    "  kdx=k-div(nz,2);\n",
+    "  rr=round(Int,sqrt(idx^2+jdx^2+kdx^2));\n",
+    "  if ((rr<=nl) & (rr>0))\n",
+    "   kn[rr]+=Ax2[i,j,k];\n",
+    "   kl[rr]=rr;\n",
+    "  end\n",
+    " end\n",
+    " return kn,kl\n",
+    "end\n",
+    "\n",
+    "uxc = Array(GPUprob.vars.ux);\n",
+    "uyc = Array(GPUprob.vars.uy);\n",
+    "uzc = Array(GPUprob.vars.uz);\n",
+    "E = uxc.^2 + uyc.^2 + uzc.^2;\n",
+    "y,x = spectrallines3D(E);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "surprising-merchant",
+   "metadata": {},
+   "source": [
+    "## Conclusion\n",
+    "One can see the structure of velocity become fully chaotic from its initial state (LHS figure) while a power law relationship can be observed for the energy spectrum (RHS figure). We may safety say the Tri-periodic vortrex settup caused at instability in high Re and a turbulence behavior is captured by the MHDFlow solver, in particalar both its structure and its powerlaw spectrum.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "abroad-detector",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "Figure(PyObject <Figure size 1200x600 with 2 Axes>)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "PyObject <matplotlib.legend.Legend object at 0x7f8a9176b828>"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "figure(figsize=(12,6))\n",
+    "subplot(121)\n",
+    "imshow(uxc[:,:,5])\n",
+    "title(L\"U_x\",size=16)\n",
+    "subplot(122)\n",
+    "loglog(x,y,\"o\",label=\"Spectrum\");\n",
+    "loglog(x[5:50],y[5]*x[5:50].^(-5/3)*100,\"k--\",label=L\"k^{5/3}\")\n",
+    "ylabel(L\"P_k}\",size=16)\n",
+    "xlabel(L\"k\",size=16)\n",
+    "title(L\"Energy Spectrum\",size=16)\n",
+    "grid()\n",
+    "legend(fontsize=16)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "heated-things",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "@webio": {
+   "lastCommId": "02182625-4c3b-4ac3-8b89-13ff33536a83",
+   "lastKernelId": "42c7a332-2f19-45de-9027-9f7f688734aa"
+  },
+  "kernelspec": {
+   "display_name": "Julia 4 Threads 1.5.3",
+   "language": "julia",
+   "name": "julia-4-threads-1.5"
+  },
+  "language_info": {
+   "file_extension": ".jl",
+   "mimetype": "application/julia",
+   "name": "julia",
+   "version": "1.5.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/img/TG_Instability.gif b/img/TG_Instability.gif
new file mode 100644
index 0000000..f76c2c0
Binary files /dev/null and b/img/TG_Instability.gif differ
diff --git a/src/HDSolver.jl b/src/HDSolver.jl
new file mode 100644
index 0000000..427bbe7
--- /dev/null
+++ b/src/HDSolver.jl
@@ -0,0 +1,126 @@
+module HDSolver
+
+export 
+	UᵢUpdate!,
+	HDcalcN_advection!,
+	HDupdatevars!
+
+
+using
+  CUDA,
+  Reexport,
+  DocStringExtensions
+
+@reexport using FourierFlows
+
+using LinearAlgebra: mul!, ldiv!
+using FourierFlows: parsevalsum
+
+
+# δ function
+δ(a::Int,b::Int) = ( a == b ? 1 : 0 );
+
+
+function UᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="x")
+
+  if direction == "x"
+
+  	# a = {1,2,3} -> {x,y,z} direction
+  	a    = 1;
+  	kₐ   = grid.kr;
+  	k⁻²  = grid.invKrsq;
+  	uᵢh  = vars.uxh;
+  	∂uᵢh∂t = @view N[:,:,:,params.ux_ind];
+
+  elseif direction == "y"
+
+  	a    = 2;
+  	kₐ   = grid.l;
+  	k⁻²  = grid.invKrsq;
+  	uᵢh  = vars.uyh;
+  	∂uᵢh∂t = @view N[:,:,:,params.uy_ind];
+    
+  elseif direction == "z"
+
+  	a    = 3;
+  	kₐ   = grid.m;
+  	k⁻²  = grid.invKrsq;
+  	uᵢh  = vars.uzh;
+  	∂uᵢh∂t = @view N[:,:,:,params.uz_ind];
+
+  else
+
+  	@warn "Warning : Unknown direction is declerad"
+
+  end
+
+  @. ∂uᵢh∂t*= 0;
+
+  for (uᵢ,kᵢ) ∈ zip([vars.ux,vars.uy,vars.uz],[grid.kr,grid.l,grid.m])
+        for (uⱼ,kⱼ,j) ∈ zip([vars.ux,vars.uy,vars.uz],[grid.kr,grid.l,grid.m],[1, 2, 3])
+
+          # Initialization 
+          @. vars.nonlin1 *= 0;
+          @. vars.nonlin2 *= 0;
+          uᵢuⱼ  = vars.nonlin1;    
+          uᵢuⱼh = vars.nonlinh1;
+          
+          # Pre-Calculation in Real Space
+          @. uᵢuⱼ = uᵢ*uⱼ;
+
+          # Fourier transform 
+          mul!(uᵢuⱼh, grid.rfftplan, uᵢuⱼ);
+          
+          # Perform the actual calculation
+          @. ∂uᵢh∂t += -im*kᵢ*(δ(a,j)-kₐ*kⱼ*k⁻²)*uᵢuⱼh;
+            
+        end
+    end
+    
+    #Compute the diffusion term  - νk^2 u_i
+    @. ∂uᵢh∂t += -grid.Krsq*params.ν*uᵢh;
+    return nothing
+    
+end
+
+function HDcalcN_advection!(N, sol, t, clock, vars, params, grid)
+
+  #Update V  Fourier Conponment
+  @. vars.uxh = sol[:, :, :, params.ux_ind];
+  @. vars.uyh = sol[:, :, :, params.uy_ind];
+  @. vars.uzh = sol[:, :, :, params.uz_ind];
+    
+
+  #Update V + B Real Conponment
+  ldiv!(vars.ux, grid.rfftplan, deepcopy(vars.uxh))
+  ldiv!(vars.uy, grid.rfftplan, deepcopy(vars.uyh))
+  ldiv!(vars.uz, grid.rfftplan, deepcopy(vars.uzh))
+  
+  #Update V Advection
+  UᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="x")
+  UᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="y")
+  UᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="z")
+  
+  return nothing
+end
+
+function HDupdatevars!(prob)
+  vars, grid, sol, params = prob.vars, prob.grid, prob.sol, prob.params
+  
+  dealias!(sol, grid)
+  
+  #Update V Fourier Conponment
+  @. vars.uxh = sol[:, :, :, params.ux_ind];
+  @. vars.uyh = sol[:, :, :, params.uy_ind];
+  @. vars.uzh = sol[:, :, :, params.uz_ind];
+
+
+  #Update V + B Real Conponment
+  ldiv!(vars.ux, grid.rfftplan, deepcopy(vars.uxh)) # deepcopy() since inverse real-fft destroys its input
+  ldiv!(vars.uy, grid.rfftplan, deepcopy(vars.uyh)) # deepcopy() since inverse real-fft destroys its input
+  ldiv!(vars.uz, grid.rfftplan, deepcopy(vars.uzh)) # deepcopy() since inverse real-fft destroys its input
+ 
+  return nothing
+end
+
+end
diff --git a/src/MHDFlows.jl b/src/MHDFlows.jl
index 7f39874..d06d241 100644
--- a/src/MHDFlows.jl
+++ b/src/MHDFlows.jl
@@ -10,12 +10,14 @@ using
 @reexport using FourierFlows
 
 include("pgen.jl")
-include("Solver.jl")
+include("MHDSolver.jl")
+include("HDSolver.jl")
 include("datastructure.jl")
 include("integrator.jl")
 
 @reexport using MHDFlows.pgen
 @reexport using MHDFlows.MHDSolver
+@reexport using MHDFlows.HDSolver
 @reexport using MHDFlows.datastructure
 @reexport using MHDFlows.integrator
 
diff --git a/src/MHDSolver.jl b/src/MHDSolver.jl
new file mode 100644
index 0000000..0a85e16
--- /dev/null
+++ b/src/MHDSolver.jl
@@ -0,0 +1,212 @@
+module MHDSolver
+
+export 
+	UᵢUpdate!,
+	BᵢUpdate!,
+	MHDcalcN_advection!,
+	MHDupdatevars!
+
+
+using
+  CUDA,
+  Reexport,
+  DocStringExtensions
+
+@reexport using FourierFlows
+
+using LinearAlgebra: mul!, ldiv!
+using FourierFlows: parsevalsum
+
+
+# δ function
+δ(a::Int,b::Int) = ( a == b ? 1 : 0 );
+
+function UᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="x")
+
+  if direction == "x"
+
+  	# a = {1,2,3} -> {x,y,z} direction
+  	a    = 1;
+  	kₐ   = grid.kr;
+  	k⁻²  = grid.invKrsq;
+  	uᵢh  = vars.uxh;
+  	∂uᵢh∂t = @view N[:,:,:,params.ux_ind];
+
+  elseif direction == "y"
+
+  	a    = 2;
+  	kₐ   = grid.l;
+  	k⁻²  = grid.invKrsq;
+  	uᵢh  = vars.uyh;
+  	∂uᵢh∂t = @view N[:,:,:,params.uy_ind];
+
+  elseif direction == "z"
+
+  	a    = 3;
+  	kₐ   = grid.m;
+  	k⁻²  = grid.invKrsq;
+  	uᵢh  = vars.uzh;
+  	∂uᵢh∂t = @view N[:,:,:,params.uz_ind];
+
+  else
+
+  	@warn "Warning : Unknown direction is declerad"
+
+  end
+
+  @. ∂uᵢh∂t*= 0;
+
+  for (bᵢ,uᵢ,kᵢ) ∈ zip([vars.bx,vars.by,vars.bz],[vars.ux,vars.uy,vars.uz],[grid.kr,grid.l,grid.m])
+        for (bⱼ,uⱼ,kⱼ,j) ∈ zip([vars.bx,vars.by,vars.bz],[vars.ux,vars.uy,vars.uz],[grid.kr,grid.l,grid.m],[1, 2, 3])
+
+          # Initialization 
+          @. vars.nonlin1 *= 0;
+          @. vars.nonlin2 *= 0;
+          uᵢuⱼ  = vars.nonlin1;    
+          bᵢbⱼ  = vars.nonlin2; 
+          uᵢuⱼh = vars.nonlinh1;
+          bᵢbⱼh = vars.nonlinh2;
+          
+          # Pre-Calculation in Real Space
+          @. uᵢuⱼ = uᵢ*uⱼ;
+          @. bᵢbⱼ = bᵢ*bⱼ;;
+
+          # Fourier transform 
+          mul!(uᵢuⱼh, grid.rfftplan, uᵢuⱼ);
+          mul!(bᵢbⱼh, grid.rfftplan, bᵢbⱼ);
+          
+          # Perform the actual calculation
+          @. ∂uᵢh∂t += -im*kᵢ*(δ(a,j)-kₐ*kⱼ*k⁻²)*(uᵢuⱼh-bᵢbⱼh);
+            
+        end
+    end
+    
+    #Compute the diffusion term  - νk^2 u_i
+    @. ∂uᵢh∂t += -grid.Krsq*params.ν*uᵢh;
+    return nothing
+    
+end
+
+# B function
+function BᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="x")
+
+	#To Update B_i, we have two terms to compute:
+	# ∂B_i/∂t = im ∑_j k_j*(b_iu_j - u_ib_j)  - η k^2 B_i
+	#We split two terms for sparating the computation.
+
+  # declare the var u_i, b_i for computation
+	if direction == "x"
+
+		uᵢ  = vars.ux;
+		bᵢ  = vars.bx; 
+		bᵢh = vars.bxh; 
+		∂Bᵢh∂t = @view N[:,:,:,params.bx_ind];
+
+	elseif direction == "y"
+
+		uᵢ  = vars.uy;
+		bᵢ  = vars.by; 
+		bᵢh = vars.byh; 
+		∂Bᵢh∂t = @view N[:,:,:,params.by_ind];
+
+	elseif direction == "z"
+
+		uᵢ  = vars.uz;
+		bᵢ  = vars.bz; 
+		bᵢh = vars.bzh; 
+		∂Bᵢh∂t = @view N[:,:,:,params.bz_ind];
+
+	else
+
+		@warn "Warning : Unknown direction is declerad"
+
+	end
+
+    @. ∂Bᵢh∂t*= 0;
+    
+    #Compute the first term, im ∑_j k_j*(b_iu_j - u_ib_j)
+    for (bⱼ,uⱼ,kⱼ) ∈ zip([vars.bx,vars.by,vars.bz],[vars.ux,vars.uy,vars.uz],[grid.kr,grid.l,grid.m])
+
+        # Initialization 
+        @. vars.nonlin1 *= 0;
+        @. vars.nonlin2 *= 0;
+        uᵢbⱼ  = vars.nonlin1;    
+        bᵢuⱼ  = vars.nonlin2; 
+        uᵢbⱼh = vars.nonlinh1;
+        bᵢuⱼh = vars.nonlinh2;
+        
+        # Pre-Calculation in Real Space
+        @. uᵢbⱼ = uᵢ*bⱼ;
+        @. bᵢuⱼ = bᵢ*uⱼ;
+        # Fourier transform back to spectral space
+        mul!(uᵢbⱼh, grid.rfftplan, uᵢbⱼ);
+        mul!(bᵢuⱼh, grid.rfftplan, bᵢuⱼ);
+        
+        @. ∂Bᵢh∂t += -im*kⱼ*(bᵢuⱼh - uᵢbⱼh);
+    end
+    
+    #Compute the diffusion term  - ηk^2 B_i
+    @. ∂Bᵢh∂t += -grid.Krsq*params.η*bᵢh;
+    
+    return nothing
+
+end
+
+function MHDcalcN_advection!(N, sol, t, clock, vars, params, grid)
+
+  #Update V + B Fourier Conponment
+  @. vars.uxh = sol[:, :, :, params.ux_ind];
+  @. vars.uyh = sol[:, :, :, params.uy_ind];
+  @. vars.uzh = sol[:, :, :, params.uz_ind];
+    
+  @. vars.bxh = sol[:, :, :, params.bx_ind];
+  @. vars.byh = sol[:, :, :, params.by_ind];
+  @. vars.bzh = sol[:, :, :, params.bz_ind];
+
+  #Update V + B Real Conponment
+  ldiv!(vars.ux, grid.rfftplan, vars.uxh)
+  ldiv!(vars.uy, grid.rfftplan, vars.uyh)
+  ldiv!(vars.uz, grid.rfftplan, vars.uzh)
+  ldiv!(vars.bx, grid.rfftplan, vars.bxh)
+  ldiv!(vars.by, grid.rfftplan, vars.byh)
+  ldiv!(vars.bz, grid.rfftplan, vars.bzh)  
+  
+  #Update V Advection
+  UᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="x")
+  UᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="y")
+  UᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="z")
+  
+  #Update B Advection
+  BᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="x")
+  BᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="y")
+  BᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="z")  
+  
+  return nothing
+end
+
+function MHDupdatevars!(prob)
+  vars, grid, sol, params = prob.vars, prob.grid, prob.sol, prob.params
+  
+  dealias!(sol, grid)
+  
+  #Update V + B Fourier Conponment
+  @. vars.uxh = sol[:, :, :, params.ux_ind];
+  @. vars.uyh = sol[:, :, :, params.uy_ind];
+  @. vars.uzh = sol[:, :, :, params.uz_ind];
+    
+  @. vars.bxh = sol[:, :, :, params.bx_ind];
+  @. vars.byh = sol[:, :, :, params.by_ind];
+  @. vars.bzh = sol[:, :, :, params.bz_ind];
+
+  #Update V + B Real Conponment
+  ldiv!(vars.ux, grid.rfftplan, deepcopy(vars.uxh)) # deepcopy() since inverse real-fft destroys its input
+  ldiv!(vars.uy, grid.rfftplan, deepcopy(vars.uyh)) # deepcopy() since inverse real-fft destroys its input
+  ldiv!(vars.uz, grid.rfftplan, deepcopy(vars.uzh)) # deepcopy() since inverse real-fft destroys its input
+  ldiv!(vars.bx, grid.rfftplan, deepcopy(vars.bxh)) # deepcopy() since inverse real-fft destroys its input
+  ldiv!(vars.by, grid.rfftplan, deepcopy(vars.byh)) # deepcopy() since inverse real-fft destroys its input
+  ldiv!(vars.bz, grid.rfftplan, deepcopy(vars.bzh)) # deepcopy() since inverse real-fft destroys its input
+  
+  return nothing
+end
+
+end
diff --git a/src/datastructure.jl b/src/datastructure.jl
index 9e10c6c..9902230 100644
--- a/src/datastructure.jl
+++ b/src/datastructure.jl
@@ -130,6 +130,9 @@ struct HDParams{T} <: AbstractParams
    ux_ind :: Int
    uy_ind :: Int
    uz_ind :: Int
+
+  "function that calculates the Fourier transform of the forcing, ``F̂``"
+    calcF! :: Function
     
 end
 
diff --git a/src/integrator.jl b/src/integrator.jl
index 415e96c..ec1b6d4 100644
--- a/src/integrator.jl
+++ b/src/integrator.jl
@@ -1,6 +1,7 @@
 module integrator
 
-include("Solver.jl")
+include("MHDSolver.jl")
+include("HDSolver.jl")
 
 using
   CUDA,
diff --git a/src/pgen.jl b/src/pgen.jl
index f753b14..0e467c7 100644
--- a/src/pgen.jl
+++ b/src/pgen.jl
@@ -10,7 +10,8 @@ using
 
 @reexport using FourierFlows
 
-include("Solver.jl")
+include("MHDSolver.jl")
+include("HDSolver.jl")
 include("datastructure.jl")
 
 export MHDProblem,
@@ -22,7 +23,9 @@ export MHDProblem,
 MHDParams  = datastructure.MHDParams;
 HDParams   = datastructure.HDParams;
 SetMHDVars = datastructure.SetMHDVars;
+SetHDVars  = datastructure.SetHDVars;
 MHDcalcN_advection!  = MHDSolver.MHDcalcN_advection!;
+HDcalcN_advection!   = HDSolver.HDcalcN_advection!;
 
 nothingfunction(args...) = nothing;
 
@@ -102,7 +105,6 @@ end
 
 
 """
-**Under constrcution right now, not in use**
 function HDProblem(dev::Device=CPU();
   # Numerical parameters
                 nx = 64,
@@ -141,7 +143,6 @@ Keyword arguments
   - `T`: `Float32` or `Float64`; floating point type used for `problem` data.
 """
 
-
 function HDProblem(dev::Device=CPU();
   # Numerical parameters
                 nx = 64,
@@ -153,7 +154,6 @@ function HDProblem(dev::Device=CPU();
    # Drag and/or hyper-viscosity for velocity
                  ν = 0,
                 nν = 1,
-                 μ = 0,
    # force function 
                 calcF = nothingfunction,
   # Timestepper and equation options
@@ -164,11 +164,11 @@ function HDProblem(dev::Device=CPU();
 
   grid = ThreeDGrid(dev, nx, Lx, ny, Ly, nz, Lz; T=T)
 
-  params = HDParams{T}(ν, η, nν, 1, 2, 3, 4, 5, 6)
+  params = HDParams{T}(ν, nν, 1, 2, 3, calcF)
 
   vars = SetHDVars(dev, grid);
 
-  equation = Equation_with_forcing(dev, params, grid)
+  equation = Equation_with_forcing(dev,params, grid)
 
   return FourierFlows.Problem(equation, stepper, dt, grid, vars, params, dev)
 end
@@ -202,10 +202,11 @@ function Equation_with_forcing(dev,params::MHDParams, grid::AbstractGrid)
 end
 
 function Equation_with_forcing(dev,params::HDParams, grid::AbstractGrid)
+  
   T = eltype(grid)
   L = zeros(dev, T, (grid.nkr,grid.nm,grid.nk, 6));
     
-  return FourierFlows.Equation(L,MHDcalcN!, grid)
+  return FourierFlows.Equation(L,HDcalcN!, grid)
 end
 
 function addforcing!(N, sol, t, clock, vars, params, grid)