Merge pull request #758 from mkstoyanov/add_refine_benchmark

added benchamrk to test refinement

SparseGrids/Benchmarks/benchCommon.hpp

@@ -12,7 +12,8 @@ enum BenchFuction{
     bench_evaluate,
     bench_evaluate_mixed,
     bench_differentiate,
-    bench_iweights
+    bench_iweights,
+    bench_refine
 };
 
 BenchFuction getTest(std::string const &s){
@@ -22,7 +23,8 @@ BenchFuction getTest(std::string const &s){
         {"differentiate", bench_differentiate},
         {"loadneeded", bench_loadneeded},
         {"makegrid", bench_make},
-        {"iweights", bench_iweights}
+        {"iweights", bench_iweights},
+        {"refine", bench_refine}
     };
 
     try{
@@ -68,6 +70,11 @@ template<typename StringListIterator>
 void readEntry(StringListIterator &iter, int &val){
     val = std::stoi(*iter++);
 }
+//! \brief Convert a string to double and advance the iterator.
+template<typename StringListIterator>
+void readEntry(StringListIterator &iter, double &val){
+    val = std::stod(*iter++);
+}
 //! \brief Convert a string to TypeDepth and advance the iterator.
 template<typename StringListIterator>
 void readEntry(StringListIterator &iter, TypeDepth &val){
@@ -78,6 +85,11 @@ template<typename StringListIterator>
 void readEntry(StringListIterator &iter, TypeOneDRule &val){
     val = IO::getRuleString(*iter++);
 }
+//! \brief Convert a string to TypeRefinement and advance the iterator.
+template<typename StringListIterator>
+void readEntry(StringListIterator &iter, TypeRefinement &val){
+    val = IO::getTypeRefinementString(*iter++);
+}
 //! \brief Convert a string to TypeAcceleration and advance the iterator.
 template<typename StringListIterator>
 void readEntry(StringListIterator &iter, TypeAcceleration &val){

SparseGrids/Benchmarks/benchRefine.hpp

@@ -0,0 +1,59 @@
+#ifndef _TASMANIAN_BENCHMARK_REFINE_HPP
+#define _TASMANIAN_BENCHMARK_REFINE_HPP
+
+#include "benchCommon.hpp"
+
+bool benchmark_refine(std::deque<std::string> &args){
+    if (args.size() < 15) return false;
+
+    // report the test parameters to reference later
+    cout << "refine";
+    for(auto &s : args) cout << " " << s;
+
+    auto grid_family = getGridFamily(args);
+    if (grid_family == GridFamily::none) return false;
+
+    int num_dimensions, num_outputs, num_depth, order, iteratons;
+    TypeDepth dtype;
+    TypeOneDRule rule;
+    TypeAcceleration acc;
+    int device;
+
+    TypeDepth ref_aniso_type;
+    int aniso_min_growth;
+    double surp_tolerance;
+    TypeRefinement surp_criteria;
+    int output;
+
+    auto riter = readEntries(args.begin(), num_dimensions, num_outputs, num_depth, dtype, rule, order,
+                             ref_aniso_type, aniso_min_growth, surp_tolerance, surp_criteria, output, iteratons, acc, device);
+
+    std::string flavor = checkFlavor(riter, args.end());
+
+    auto extra = extractWeightsLimits(grid_family, num_dimensions, dtype, riter, args.end());
+
+    auto make_grid = getLambdaMakeGrid(grid_family, num_dimensions, num_outputs, num_depth, dtype, rule, order, extra);
+
+    auto grid = make_grid();
+    cout << " (points: " << grid.getNumPoints() << ")\n";
+    loadGenericModel(grid);
+
+    grid.enableAcceleration(acc, device);
+    if (flavor != "auto")
+        grid.favorSparseAcceleration((flavor == "sparse"));
+
+    auto test_lambda = [&](int)->void{
+            if (aniso_min_growth < 1) {
+                grid.setSurplusRefinement(surp_tolerance, surp_criteria, output);
+            } else {
+                grid.setAnisotropicRefinement(ref_aniso_type, aniso_min_growth, output);
+            }
+        };
+
+    // make one dry-run
+    cout << setw(7) << testMethod<DryRun>(iteratons, test_lambda) << endl;
+
+    return true;
+}
+
+#endif

SparseGrids/Benchmarks/bench_main.cpp

@@ -3,6 +3,7 @@
 #include "benchEvaluate.hpp"
 #include "benchDifferentiate.hpp"
 #include "benchInterpolationWeights.hpp"
+#include "benchRefine.hpp"
 
 void printHelp(BenchFuction test);
 
@@ -42,6 +43,9 @@ int main(int argc, const char** argv){
         case bench_iweights:
             pass = benchmark_iweights(args);
             break;
+        case bench_refine:
+            pass = benchmark_refine(args);
+            break;
         default:
             throw std::runtime_error("bench_main.cpp: invalid test type in switch statement!");
     }
@@ -55,7 +59,7 @@ int main(int argc, const char** argv){
 void printHelp(BenchFuction test){
     if (test == bench_none){
         cout << "\nusage: ./benchmark <function> <parameters>\n\n";
-        cout << "functions: makegrid, loadneeded, evaluate(-mixed), differentiate, iweights\n";
+        cout << "functions: makegrid, loadneeded, evaluate(-mixed), differentiate, iweights, refine\n";
         cout << "\n see: ./benchmark <function> help\n";
     }else if (test == bench_make){
         cout << "\nusage: ./benchmark makegrid <grid> <dims> <depth> <type> <rule> <iters> <jumps> <aniso>\n\n";
@@ -124,6 +128,27 @@ void printHelp(BenchFuction test){
         cout << "jumps : how many times to increase <depth> by 1\n";
         cout << "aniso : (optional) list of anisotropic weights and level limits\n";
         cout << "      : anisotropic weights come first (if used by the grid), then level limits\n";
+    }else if (test == bench_refine){
+        cout << "\nusage: ./benchmark refine <grid> <dims> <outs> <depth> <type> <rule> <order> <ref-type-depth> <min-growth> <surp-tolerance> <surp-criteria> <output> <iters> <acc> <gpu> <extra>\n\n";
+        cout << "grid  : global, sequence, localp, wavelet, fourier\n";
+        cout << "dims  : number of dimensions\n";
+        cout << "outs  : number of outputs\n";
+        cout << "depth : grid density\n";
+        cout << "type  : level, iptotal, etc.; ignored if not used by the grid\n";
+        cout << "rule  : rleja, clenshaw-curtis, etc.; ignored for wavelet and fourier grids\n";
+        cout << "order : -1, 0, 1, 2; ignored if not used by the grid\n\n";
+
+        cout << "ref-type-depth : (anisotropic refinement) refinement type, e.g., iptotal, ipcurved\n";
+        cout << "min-growth     : (anisotropic refinement) minumum number of refinement points, use 0 to switch to surplus refinement\n";
+        cout << "surp-tolerance : (surplus refinement) tolerance\n";
+        cout << "surp-criteria  : (surplus refinement) selection criteria, e.g., stable, fds\n";
+        cout << "output         : (all refinement) output to use in the refinement\n\n";
+
+        cout << "iters : number of times to repeat the function call\n";
+        cout << "acc   : acceleration type, e.g., gpu-cuda, cpu-blas, none, etc.\n";
+        cout << "gpu   : cuda device ID; ignored for cpu acceleration\n";
+        cout << "extra : (optional) list of anisotropic weights and level limits\n";
+        cout << "      : anisotropic weights come first (if used by the grid), then level limits\n";
     }
     cout << endl;
 }

SparseGrids/CMakeLists.txt

@@ -91,6 +91,7 @@ add_executable(Tasmanian_benchmarksgrid  Benchmarks/benchCommon.hpp
                                          Benchmarks/benchLoadNeeded.hpp
                                          Benchmarks/benchDifferentiate.hpp
                                          Benchmarks/benchEvaluate.hpp
+                                         Benchmarks/benchRefine.hpp
                                          Benchmarks/bench_main.cpp)
 
 if (Tasmanian_ENABLE_CUDA)

SparseGrids/tsgGridLocalPolynomial.cpp

@@ -1273,7 +1273,6 @@ Data2D<int> GridLocalPolynomial::buildUpdateMap(double tolerance, TypeRefinement
             int nump = split.getJobNumPoints(j);
             const int *pnts = split.getJobPoints(j);
 
-
             std::vector<int> levels(nump);
 
             int max_level = 0;