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remove splitk from exhaustive tuning (#3272)
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-13
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3 files changed

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-13
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CHANGELOG.md

Lines changed: 0 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -14,7 +14,6 @@ Full documentation for MIGraphX is available at
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* Added a `--test` flag in migraphx-driver to validate the installation
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* Added support for ONNX Operator: Einsum
1616
* Added uint8 support in ONNX Operators
17-
* Enabled Split-k kernel configurations for performance improvements
1817
* Added fusion for group convolutions
1918
* Added rocMLIR conv3d support
2019
* Added rocgdb to the Dockerfile
@@ -46,7 +45,6 @@ Full documentation for MIGraphX is available at
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* Added support for multi outputs in pointwise ops
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* Improve reduction fusion with reshape operators
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* Use the quantized output when an operator is used again
49-
* Enabled Split-k GEMM perf configs for rocMLIR based GEMM kernels for better performance on all Hardware
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### Fixes

src/targets/gpu/mlir.cpp

Lines changed: 1 addition & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -595,8 +595,7 @@ struct mlir_program
595595
{"sym_name", sym_name},
596596
{"kernel", std::string("mixr")},
597597
{"arch", target_arch},
598-
{"num_cu", num_cu},
599-
{"enable_splitk_for_tuning", true}});
598+
{"num_cu", num_cu}});
600599
ops.add_region(std::move(region));
601600
insert(body, std::move(ops));
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test/gpu/mlir.cpp

Lines changed: 9 additions & 9 deletions
Original file line numberDiff line numberDiff line change
@@ -158,7 +158,7 @@ TEST_CASE(conv)
158158
{
159159
const std::string mlir_output = R"__migraphx__(
160160
module {
161-
func.func @mlir_convolution(%arg0: !migraphx.shaped<2x8x3x3xf32, 72x9x3x1>, %arg1: !migraphx.shaped<1x8x4x4xf32, 128x16x4x1>) -> !migraphx.shaped<1x2x2x2xf32, 8x4x2x1> attributes {arch = "", enable_splitk_for_tuning = true, kernel = "mixr", num_cu = 0 : i64} {
161+
func.func @mlir_convolution(%arg0: !migraphx.shaped<2x8x3x3xf32, 72x9x3x1>, %arg1: !migraphx.shaped<1x8x4x4xf32, 128x16x4x1>) -> !migraphx.shaped<1x2x2x2xf32, 8x4x2x1> attributes {arch = "", kernel = "mixr", num_cu = 0 : i64} {
162162
%0 = migraphx.convolution %arg1, %arg0 {dilation = [1, 1], group = 1 : i64, padding = [0, 0, 0, 0], padding_mode = 0 : i64, stride = [1, 1]} : <1x8x4x4xf32, 128x16x4x1>, <2x8x3x3xf32, 72x9x3x1> -> <1x2x2x2xf32, 8x4x2x1>
163163
return %0 : !migraphx.shaped<1x2x2x2xf32, 8x4x2x1>
164164
}
@@ -181,7 +181,7 @@ TEST_CASE(conv_nhwc)
181181
{
182182
const std::string mlir_output = R"__migraphx__(
183183
module {
184-
func.func @mlir_convolution(%arg0: !migraphx.shaped<2x8x3x3xf32, 72x1x24x8>, %arg1: !migraphx.shaped<1x8x4x4xf32, 128x1x32x8>) -> !migraphx.shaped<1x2x2x2xf32, 8x1x4x2> attributes {arch = "", enable_splitk_for_tuning = true, kernel = "mixr", num_cu = 0 : i64} {
184+
func.func @mlir_convolution(%arg0: !migraphx.shaped<2x8x3x3xf32, 72x1x24x8>, %arg1: !migraphx.shaped<1x8x4x4xf32, 128x1x32x8>) -> !migraphx.shaped<1x2x2x2xf32, 8x1x4x2> attributes {arch = "", kernel = "mixr", num_cu = 0 : i64} {
185185
%0 = migraphx.convolution %arg1, %arg0 {dilation = [1, 1], group = 1 : i64, padding = [0, 0, 0, 0], padding_mode = 0 : i64, stride = [1, 1]} : <1x8x4x4xf32, 128x1x32x8>, <2x8x3x3xf32, 72x1x24x8> -> <1x2x2x2xf32, 8x1x4x2>
186186
return %0 : !migraphx.shaped<1x2x2x2xf32, 8x1x4x2>
187187
}
@@ -204,7 +204,7 @@ TEST_CASE(conv_add_relu)
204204
{
205205
const std::string mlir_output = R"__migraphx__(
206206
module {
207-
func.func @mlir_convolution_add_relu(%arg0: !migraphx.shaped<1x2x2x2xf32, 8x4x2x1>, %arg1: !migraphx.shaped<2x8x3x3xf32, 72x9x3x1>, %arg2: !migraphx.shaped<1x8x4x4xf32, 128x16x4x1>) -> !migraphx.shaped<1x2x2x2xf32, 8x4x2x1> attributes {arch = "", enable_splitk_for_tuning = true, kernel = "mixr", num_cu = 0 : i64} {
207+
func.func @mlir_convolution_add_relu(%arg0: !migraphx.shaped<1x2x2x2xf32, 8x4x2x1>, %arg1: !migraphx.shaped<2x8x3x3xf32, 72x9x3x1>, %arg2: !migraphx.shaped<1x8x4x4xf32, 128x16x4x1>) -> !migraphx.shaped<1x2x2x2xf32, 8x4x2x1> attributes {arch = "", kernel = "mixr", num_cu = 0 : i64} {
208208
%0 = migraphx.convolution %arg2, %arg1 {dilation = [1, 1], group = 1 : i64, padding = [0, 0, 0, 0], padding_mode = 0 : i64, stride = [1, 1]} : <1x8x4x4xf32, 128x16x4x1>, <2x8x3x3xf32, 72x9x3x1> -> <1x2x2x2xf32, 8x4x2x1>
209209
%1 = migraphx.add %0, %arg0 : <1x2x2x2xf32, 8x4x2x1>, <1x2x2x2xf32, 8x4x2x1> -> <1x2x2x2xf32, 8x4x2x1>
210210
%2 = migraphx.relu %1 : <1x2x2x2xf32, 8x4x2x1> -> <1x2x2x2xf32, 8x4x2x1>
@@ -233,7 +233,7 @@ TEST_CASE(conv_reshape_dim_minus_one)
233233
{
234234
const std::string mlir_output = R"__migraphx__(
235235
module {
236-
func.func @mlir_convolution_reshape(%arg0: !migraphx.shaped<2x8x3x3xf32, 72x9x3x1>, %arg1: !migraphx.shaped<1x8x4x4xf32, 128x16x4x1>) -> !migraphx.shaped<1x4x1x2xf32, 8x2x2x1> attributes {arch = "", enable_splitk_for_tuning = true, kernel = "mixr", num_cu = 0 : i64} {
236+
func.func @mlir_convolution_reshape(%arg0: !migraphx.shaped<2x8x3x3xf32, 72x9x3x1>, %arg1: !migraphx.shaped<1x8x4x4xf32, 128x16x4x1>) -> !migraphx.shaped<1x4x1x2xf32, 8x2x2x1> attributes {arch = "", kernel = "mixr", num_cu = 0 : i64} {
237237
%0 = migraphx.convolution %arg1, %arg0 {dilation = [1, 1], group = 1 : i64, padding = [0, 0, 0, 0], padding_mode = 0 : i64, stride = [1, 1]} : <1x8x4x4xf32, 128x16x4x1>, <2x8x3x3xf32, 72x9x3x1> -> <1x2x2x2xf32, 8x4x2x1>
238238
%1 = migraphx.reshape %0 {dims = [1, 4, 1, 2]} : <1x2x2x2xf32, 8x4x2x1> -> <1x4x1x2xf32, 8x2x2x1>
239239
return %1 : !migraphx.shaped<1x4x1x2xf32, 8x2x2x1>
@@ -258,7 +258,7 @@ TEST_CASE(quant_dot_add)
258258
{
259259
const std::string mlir_output = R"__migraphx__(
260260
module {
261-
func.func @mlir_quant_dot_add(%arg0: !migraphx.shaped<1x5x4xi8, 20x4x1>, %arg1: !migraphx.shaped<1x4x3xi8, 12x3x1>, %arg2: !migraphx.shaped<1x5x3xi32, 15x3x1>) -> !migraphx.shaped<1x5x3xi32, 15x3x1> attributes {arch = "", enable_splitk_for_tuning = true, kernel = "mixr", num_cu = 0 : i64} {
261+
func.func @mlir_quant_dot_add(%arg0: !migraphx.shaped<1x5x4xi8, 20x4x1>, %arg1: !migraphx.shaped<1x4x3xi8, 12x3x1>, %arg2: !migraphx.shaped<1x5x3xi32, 15x3x1>) -> !migraphx.shaped<1x5x3xi32, 15x3x1> attributes {arch = "", kernel = "mixr", num_cu = 0 : i64} {
262262
%0 = migraphx.quant_dot %arg0, %arg1 : <1x5x4xi8, 20x4x1>, <1x4x3xi8, 12x3x1> -> <1x5x3xi32, 15x3x1>
263263
%1 = migraphx.add %0, %arg2 : <1x5x3xi32, 15x3x1>, <1x5x3xi32, 15x3x1> -> <1x5x3xi32, 15x3x1>
264264
return %1 : !migraphx.shaped<1x5x3xi32, 15x3x1>
@@ -285,7 +285,7 @@ TEST_CASE(dot_add)
285285
{
286286
const std::string mlir_output = R"__migraphx__(
287287
module {
288-
func.func @mlir_dot_add(%arg0: !migraphx.shaped<1x5x4xf32, 20x4x1>, %arg1: !migraphx.shaped<1x4x3xf32, 12x3x1>, %arg2: !migraphx.shaped<1x5x3xf32, 15x3x1>) -> !migraphx.shaped<1x5x3xf32, 15x3x1> attributes {arch = "", enable_splitk_for_tuning = true, kernel = "mixr", num_cu = 0 : i64} {
288+
func.func @mlir_dot_add(%arg0: !migraphx.shaped<1x5x4xf32, 20x4x1>, %arg1: !migraphx.shaped<1x4x3xf32, 12x3x1>, %arg2: !migraphx.shaped<1x5x3xf32, 15x3x1>) -> !migraphx.shaped<1x5x3xf32, 15x3x1> attributes {arch = "", kernel = "mixr", num_cu = 0 : i64} {
289289
%0 = migraphx.dot %arg0, %arg1 : <1x5x4xf32, 20x4x1>, <1x4x3xf32, 12x3x1> -> <1x5x3xf32, 15x3x1>
290290
%1 = migraphx.add %0, %arg2 : <1x5x3xf32, 15x3x1>, <1x5x3xf32, 15x3x1> -> <1x5x3xf32, 15x3x1>
291291
return %1 : !migraphx.shaped<1x5x3xf32, 15x3x1>
@@ -311,7 +311,7 @@ TEST_CASE(conv_int8_dequantize_quantize)
311311
{
312312
const std::string mlir_output = R"__migraphx__(
313313
module {
314-
func.func @mlir_quant_convolution_dequantizelinear_quantizelinear(%arg0: !migraphx.shaped<2x8x3x3xi8, 72x9x3x1>, %arg1: !migraphx.shaped<1x8x4x4xi8, 128x16x4x1>, %arg2: !migraphx.shaped<1x2x2x2xf32, 8x4x2x1>, %arg3: !migraphx.shaped<1x2x2x2xi32, 8x4x2x1>) -> !migraphx.shaped<1x2x2x2xi32, 8x4x2x1> attributes {arch = "", enable_splitk_for_tuning = true, kernel = "mixr", num_cu = 0 : i64} {
314+
func.func @mlir_quant_convolution_dequantizelinear_quantizelinear(%arg0: !migraphx.shaped<2x8x3x3xi8, 72x9x3x1>, %arg1: !migraphx.shaped<1x8x4x4xi8, 128x16x4x1>, %arg2: !migraphx.shaped<1x2x2x2xf32, 8x4x2x1>, %arg3: !migraphx.shaped<1x2x2x2xi32, 8x4x2x1>) -> !migraphx.shaped<1x2x2x2xi32, 8x4x2x1> attributes {arch = "", kernel = "mixr", num_cu = 0 : i64} {
315315
%0 = migraphx.quant_convolution %arg1, %arg0 {dilation = [1, 1], group = 1 : i64, padding = [0, 0, 0, 0], padding_mode = 0 : i64, stride = [1, 1]} : <1x8x4x4xi8, 128x16x4x1>, <2x8x3x3xi8, 72x9x3x1> -> <1x2x2x2xi32, 8x4x2x1>
316316
%1 = migraphx.dequantizelinear %0, %arg2, %arg3 : <1x2x2x2xi32, 8x4x2x1>, <1x2x2x2xf32, 8x4x2x1>, !migraphx.shaped<1x2x2x2xi32, 8x4x2x1> -> <1x2x2x2xf32, 8x4x2x1>
317317
%2 = migraphx.quantizelinear %1, %arg2, %arg3 : <1x2x2x2xf32, 8x4x2x1>, <1x2x2x2xf32, 8x4x2x1>, !migraphx.shaped<1x2x2x2xi32, 8x4x2x1> -> <1x2x2x2xi32, 8x4x2x1>
@@ -344,7 +344,7 @@ TEST_CASE(dot_convert)
344344
{
345345
const std::string mlir_output = R"__migraphx__(
346346
module {
347-
func.func @mlir_dot_convert(%arg0: !migraphx.shaped<1x5x4xf32, 20x4x1>, %arg1: !migraphx.shaped<1x4x3xf32, 12x3x1>) -> !migraphx.shaped<1x5x3xf16, 15x3x1> attributes {arch = "", enable_splitk_for_tuning = true, kernel = "mixr", num_cu = 0 : i64} {
347+
func.func @mlir_dot_convert(%arg0: !migraphx.shaped<1x5x4xf32, 20x4x1>, %arg1: !migraphx.shaped<1x4x3xf32, 12x3x1>) -> !migraphx.shaped<1x5x3xf16, 15x3x1> attributes {arch = "", kernel = "mixr", num_cu = 0 : i64} {
348348
%0 = migraphx.dot %arg0, %arg1 : <1x5x4xf32, 20x4x1>, <1x4x3xf32, 12x3x1> -> <1x5x3xf32, 15x3x1>
349349
%1 = migraphx.convert %0 {target_type = 1 : i64} : <1x5x3xf32, 15x3x1> to <1x5x3xf16, 15x3x1>
350350
return %1 : !migraphx.shaped<1x5x3xf16, 15x3x1>
@@ -370,7 +370,7 @@ TEST_CASE(dot_where)
370370
{
371371
const std::string mlir_output = R"__migraphx__(
372372
module {
373-
func.func @mlir_dot_where(%arg0: !migraphx.shaped<1x5x4xf32, 20x4x1>, %arg1: !migraphx.shaped<1x4x3xf32, 12x3x1>, %arg2: !migraphx.shaped<1x5x3xi8, 15x3x1>, %arg3: !migraphx.shaped<1x5x3xf32, 15x3x1>) -> !migraphx.shaped<1x5x3xf32, 15x3x1> attributes {arch = "", enable_splitk_for_tuning = true, kernel = "mixr", num_cu = 0 : i64} {
373+
func.func @mlir_dot_where(%arg0: !migraphx.shaped<1x5x4xf32, 20x4x1>, %arg1: !migraphx.shaped<1x4x3xf32, 12x3x1>, %arg2: !migraphx.shaped<1x5x3xi8, 15x3x1>, %arg3: !migraphx.shaped<1x5x3xf32, 15x3x1>) -> !migraphx.shaped<1x5x3xf32, 15x3x1> attributes {arch = "", kernel = "mixr", num_cu = 0 : i64} {
374374
%0 = migraphx.dot %arg0, %arg1 : <1x5x4xf32, 20x4x1>, <1x4x3xf32, 12x3x1> -> <1x5x3xf32, 15x3x1>
375375
%1 = migraphx.where %arg2, %0, %arg3 : <1x5x3xi8, 15x3x1>, <1x5x3xf32, 15x3x1>, <1x5x3xf32, 15x3x1> -> <1x5x3xf32, 15x3x1>
376376
return %1 : !migraphx.shaped<1x5x3xf32, 15x3x1>

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