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[mlir][spirv] Add an argmax integration test with
mlir-vulkan-runner
(
llvm#106426) This PR adds an integration test for an argmax kernel with `mlir-vulkan-runner`. This test exercises the `convert-to-spirv` pass (landed in llvm#95942) and demonstrates that we can use SPIR-V ops as "intrinsics" among higher-level dialects. The support for `index` dialect in `mlir-vulkan-runner` is also added.
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// RUN: mlir-vulkan-runner %s \ | ||
// RUN: --shared-libs=%vulkan-runtime-wrappers,%mlir_runner_utils \ | ||
// RUN: --entry-point-result=void | FileCheck %s | ||
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// This kernel computes the argmax (index of the maximum element) from an array | ||
// of integers. Each thread computes a lane maximum using a single `scf.for`. | ||
// Then `gpu.subgroup_reduce` is used to find the maximum across the entire | ||
// subgroup, which is then used by SPIR-V subgroup ops to compute the argmax | ||
// of the entire input array. Note that this kernel only works if we have a | ||
// single workgroup. | ||
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// CHECK: [15] | ||
module attributes { | ||
gpu.container_module, | ||
spirv.target_env = #spirv.target_env< | ||
#spirv.vce<v1.3, [Shader, Groups, GroupNonUniformArithmetic, GroupNonUniformBallot], [SPV_KHR_storage_buffer_storage_class]>, #spirv.resource_limits<>> | ||
} { | ||
gpu.module @kernels { | ||
gpu.func @kernel_argmax(%input : memref<128xi32>, %output : memref<1xi32>, %total_count_buf : memref<1xi32>) kernel | ||
attributes {spirv.entry_point_abi = #spirv.entry_point_abi<workgroup_size = [32, 1, 1]>} { | ||
%idx0 = arith.constant 0 : index | ||
%idx1 = arith.constant 1 : index | ||
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%total_count = memref.load %total_count_buf[%idx0] : memref<1xi32> | ||
%lane_count_idx = gpu.subgroup_size : index | ||
%lane_count_i32 = index.castu %lane_count_idx : index to i32 | ||
%lane_id_idx = gpu.thread_id x | ||
%lane_id_i32 = index.castu %lane_id_idx : index to i32 | ||
%lane_res_init = arith.constant 0 : i32 | ||
%lane_max_init = memref.load %input[%lane_id_idx] : memref<128xi32> | ||
%num_batches_i32 = arith.divui %total_count, %lane_count_i32 : i32 | ||
%num_batches_idx = index.castu %num_batches_i32 : i32 to index | ||
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%lane_res, %lane_max = scf.for %iter = %idx1 to %num_batches_idx step %idx1 | ||
iter_args(%lane_res_iter = %lane_res_init, %lane_max_iter = %lane_max_init) -> (i32, i32) { | ||
%iter_i32 = index.castu %iter : index to i32 | ||
%mul = arith.muli %lane_count_i32, %iter_i32 : i32 | ||
%idx_i32 = arith.addi %mul, %lane_id_i32 : i32 | ||
%idx = index.castu %idx_i32 : i32 to index | ||
%elem = memref.load %input[%idx] : memref<128xi32> | ||
%gt = arith.cmpi sgt, %elem, %lane_max_iter : i32 | ||
%lane_res_next = arith.select %gt, %idx_i32, %lane_res_iter : i32 | ||
%lane_max_next = arith.select %gt, %elem, %lane_max_iter : i32 | ||
scf.yield %lane_res_next, %lane_max_next : i32, i32 | ||
} | ||
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%subgroup_max = gpu.subgroup_reduce maxsi %lane_max : (i32) -> (i32) | ||
%eq = arith.cmpi eq, %lane_max, %subgroup_max : i32 | ||
%ballot = spirv.GroupNonUniformBallot <Subgroup> %eq : vector<4xi32> | ||
%lsb = spirv.GroupNonUniformBallotFindLSB <Subgroup> %ballot : vector<4xi32>, i32 | ||
%cond = arith.cmpi eq, %lsb, %lane_id_i32 : i32 | ||
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scf.if %cond { | ||
memref.store %lane_res, %output[%idx0] : memref<1xi32> | ||
} | ||
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gpu.return | ||
} | ||
} | ||
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func.func @main() { | ||
// Allocate 3 buffers. | ||
%in_buf = memref.alloc() : memref<128xi32> | ||
%out_buf = memref.alloc() : memref<1xi32> | ||
%total_count_buf = memref.alloc() : memref<1xi32> | ||
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// Constants. | ||
%cst0 = arith.constant 0 : i32 | ||
%idx0 = arith.constant 0 : index | ||
%idx1 = arith.constant 1 : index | ||
%idx16 = arith.constant 16 : index | ||
%idx32 = arith.constant 32 : index | ||
%idx48 = arith.constant 48 : index | ||
%idx64 = arith.constant 64 : index | ||
%idx80 = arith.constant 80 : index | ||
%idx96 = arith.constant 96 : index | ||
%idx112 = arith.constant 112 : index | ||
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// Initialize input buffer. | ||
%in_vec = arith.constant dense<[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]> : vector<16xi32> | ||
vector.store %in_vec, %in_buf[%idx0] : memref<128xi32>, vector<16xi32> | ||
vector.store %in_vec, %in_buf[%idx16] : memref<128xi32>, vector<16xi32> | ||
vector.store %in_vec, %in_buf[%idx32] : memref<128xi32>, vector<16xi32> | ||
vector.store %in_vec, %in_buf[%idx48] : memref<128xi32>, vector<16xi32> | ||
vector.store %in_vec, %in_buf[%idx64] : memref<128xi32>, vector<16xi32> | ||
vector.store %in_vec, %in_buf[%idx80] : memref<128xi32>, vector<16xi32> | ||
vector.store %in_vec, %in_buf[%idx96] : memref<128xi32>, vector<16xi32> | ||
vector.store %in_vec, %in_buf[%idx112] : memref<128xi32>, vector<16xi32> | ||
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// Initialize output buffer. | ||
%out_buf2 = memref.cast %out_buf : memref<1xi32> to memref<?xi32> | ||
call @fillResource1DInt(%out_buf2, %cst0) : (memref<?xi32>, i32) -> () | ||
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// Total number of scalars. | ||
%total_count = arith.constant 128 : i32 | ||
%total_count_buf2 = memref.cast %total_count_buf : memref<1xi32> to memref<?xi32> | ||
call @fillResource1DInt(%total_count_buf2, %total_count) : (memref<?xi32>, i32) -> () | ||
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// Launch kernel function and print output. | ||
gpu.launch_func @kernels::@kernel_argmax | ||
blocks in (%idx1, %idx1, %idx1) threads in (%idx32, %idx1, %idx1) | ||
args(%in_buf : memref<128xi32>, %out_buf : memref<1xi32>, %total_count_buf : memref<1xi32>) | ||
%out_buf3 = memref.cast %out_buf2 : memref<?xi32> to memref<*xi32> | ||
call @printMemrefI32(%out_buf3) : (memref<*xi32>) -> () | ||
return | ||
} | ||
func.func private @fillResource1DInt(%0 : memref<?xi32>, %1 : i32) | ||
func.func private @printMemrefI32(%ptr : memref<*xi32>) | ||
} |
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