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CUTLASS 2.1 (#83)

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CUTLASS 2.1 contributes:
- BLAS-style host-side API added to CUTLASS Library
- Planar Complex GEMM kernels targeting Volta and Turing Tensor Cores
- Minor enhancements and bug fixes
This commit is contained in:
Andrew Kerr
2020-04-07 13:51:25 -07:00
committed by GitHub
parent 7c0cd26d13
commit 96dab34ad9
196 changed files with 20653 additions and 1995 deletions
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test/unit/gemm/device/testbed.h
+16 -26
View File
@@ -26,6 +26,8 @@
\brief Tests for device-wide GEMM interface
*/
#pragma once
#include <iostream>
#include <fstream>
#include <sstream>
@@ -41,20 +43,7 @@
#include "cutlass/util/reference/host/tensor_norm.h"
#include "cutlass/util/reference/host/gemm.h"
inline char const *to_string(cutlass::Status status) {
switch (status) {
case cutlass::Status::kSuccess: return "kSuccess";
case cutlass::Status::kErrorMisalignedOperand: return "kErrorMisalignedOperand";
case cutlass::Status::kErrorInvalidLayout: return "kErrorInvalidLayout";
case cutlass::Status::kErrorInvalidProblem: return "kErrorInvalidProblem";
case cutlass::Status::kErrorNotSupported: return "kErrorNotSupported";
case cutlass::Status::kErrorWorkspaceNull: return "kErrorWorkspaceNull";
case cutlass::Status::kErrorInternal: return "kErrorInternal";
case cutlass::Status::kInvalid: return "kInvalid";
}
return "invalid";
}
#include "testbed_utils.h"
namespace test {
namespace gemm {
@@ -185,9 +174,12 @@ struct Testbed {
EXPECT_GT(cutlass::reference::host::TensorNorm(tensor_A.host_view()), 0);
EXPECT_GT(cutlass::reference::host::TensorNorm(tensor_B.host_view()), 0);
EXPECT_GT(cutlass::reference::host::TensorNorm(tensor_C.host_view()), 0);
EXPECT_GT(cutlass::reference::host::TensorNorm(tensor_D.host_view()), 0);
EXPECT_GT(cutlass::reference::host::TensorNorm(reference_D.host_view()), 0);
if (tensor_D.size() > 1)
EXPECT_GT(cutlass::reference::host::TensorNorm(tensor_D.host_view()), 0);
if (reference_D.size() > 1)
EXPECT_GT(cutlass::reference::host::TensorNorm(reference_D.host_view()), 0);
bool passed = cutlass::reference::host::TensorEquals(reference_D.host_view(), tensor_D.host_view());
@@ -341,18 +333,12 @@ bool TestAllGemm() {
(cutlass::platform::is_same<typename Gemm::LayoutA, cutlass::layout::RowMajor>::value ||
cutlass::platform::is_same<typename Gemm::LayoutB, cutlass::layout::ColumnMajor>::value) ? 4 : kAlignment;
int problem_size_m[] = {
kAlignmentM, 512 - 3*kAlignmentM
};
int problem_size_m[] = {kAlignmentM, 512 - 3 * kAlignmentM};
int problem_size_n[] = {
kAlignmentN, 512 - 2*kAlignmentN
};
int problem_size_n[] = {kAlignmentN, 512 - 2 * kAlignmentN};
int problem_size_k[] = {
kAlignmentK, Gemm::ThreadblockShape::kK * Gemm::kStages - kAlignmentK
};
kAlignmentK, Gemm::ThreadblockShape::kK * (Gemm::kStages + 1) - kAlignmentK};
int split_k_slices[] = {
1, 2, 3
@@ -379,6 +365,10 @@ bool TestAllGemm() {
continue;
}
if (split_k > 1 && k / Gemm::ThreadblockShape::kK < split_k) {
continue;
}
for (auto alpha : problem_alpha) {
for (auto beta : problem_beta) {