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[samples] Add
big_matvec sample with pre-existing lowering config (#…
…126) Used to be part of an experiment but likely also useful as a sample for others.
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,5 +1,6 @@ | ||
| include(quidditch_module) | ||
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||
| add_subdirectory(big_matvec) | ||
| add_subdirectory(nsnet2) | ||
| add_subdirectory(util) | ||
| add_subdirectory(vec_multiply) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,12 @@ | ||
| quidditch_module(SRC big_matvec.mlir ASSERT_XDSL) | ||
|
|
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| add_executable(big_matvec_sample main.c) | ||
| target_link_libraries( | ||
| big_matvec_sample | ||
| PRIVATE | ||
| samples_util | ||
| big_matvec | ||
| snRuntime | ||
| Quidditch::dispatch::dispatch | ||
| ) | ||
|
|
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,126 @@ | ||
| builtin.module @big_matvec { | ||
| func.func @test32(%arg0: tensor<1x400xf64>, %arg1: tensor<320x400xf64>) -> tensor<1x320xf64> { | ||
| %init = tensor.empty() : tensor<1x320xf64> | ||
| %out = linalg.matmul_transpose_b { | ||
| lowering_config = #quidditch_snitch.lowering_config< | ||
| l1_tiles = [0, 32, 80], | ||
| l1_tiles_interchange = [2, 0, 1], | ||
| dual_buffer = true | ||
| > | ||
| } | ||
| ins(%arg0, %arg1 : tensor<1x400xf64>, tensor<320x400xf64>) | ||
| outs(%init : tensor<1x320xf64>) -> tensor<1x320xf64> | ||
| %out2 = linalg.generic { | ||
| indexing_maps = [ | ||
| affine_map<(d0, d1) -> (d0, d1)>, | ||
| affine_map<(d0, d1) -> (d0, d1)> | ||
| ], iterator_types = ["parallel", "parallel"] | ||
| } ins(%out : tensor<1x320xf64>) outs(%out : tensor<1x320xf64>) { | ||
| ^bb0(%element : f64, %outs : f64): | ||
| %bias = arith.constant 5.0 : f64 | ||
| %added = arith.addf %element, %bias : f64 | ||
| linalg.yield %added : f64 | ||
| } -> tensor<1x320xf64> | ||
| func.return %out2 : tensor<1x320xf64> | ||
| } | ||
|
|
||
| func.func @test40(%arg0: tensor<1x400xf64>, %arg1: tensor<320x400xf64>) -> tensor<1x320xf64> { | ||
| %init = tensor.empty() : tensor<1x320xf64> | ||
| %out = linalg.matmul_transpose_b { | ||
| lowering_config = #quidditch_snitch.lowering_config< | ||
| l1_tiles = [0, 40, 80], | ||
| l1_tiles_interchange = [2, 0, 1], | ||
| dual_buffer = true | ||
| > | ||
| } | ||
| ins(%arg0, %arg1 : tensor<1x400xf64>, tensor<320x400xf64>) | ||
| outs(%init : tensor<1x320xf64>) -> tensor<1x320xf64> | ||
| %out2 = linalg.generic { | ||
| indexing_maps = [ | ||
| affine_map<(d0, d1) -> (d0, d1)>, | ||
| affine_map<(d0, d1) -> (d0, d1)> | ||
| ], iterator_types = ["parallel", "parallel"] | ||
| } ins(%out : tensor<1x320xf64>) outs(%out : tensor<1x320xf64>) { | ||
| ^bb0(%element : f64, %outs : f64): | ||
| %bias = arith.constant 5.0 : f64 | ||
| %added = arith.addf %element, %bias : f64 | ||
| linalg.yield %added : f64 | ||
| } -> tensor<1x320xf64> | ||
| func.return %out2 : tensor<1x320xf64> | ||
| } | ||
|
|
||
| func.func @test64(%arg0: tensor<1x400xf64>, %arg1: tensor<320x400xf64>) -> tensor<1x320xf64> { | ||
| %init = tensor.empty() : tensor<1x320xf64> | ||
| %out = linalg.matmul_transpose_b { | ||
| lowering_config = #quidditch_snitch.lowering_config< | ||
| l1_tiles = [0, 64, 80], | ||
| l1_tiles_interchange = [2, 0, 1], | ||
| dual_buffer = true | ||
| > | ||
| } | ||
| ins(%arg0, %arg1 : tensor<1x400xf64>, tensor<320x400xf64>) | ||
| outs(%init : tensor<1x320xf64>) -> tensor<1x320xf64> | ||
| %out2 = linalg.generic { | ||
| indexing_maps = [ | ||
| affine_map<(d0, d1) -> (d0, d1)>, | ||
| affine_map<(d0, d1) -> (d0, d1)> | ||
| ], iterator_types = ["parallel", "parallel"] | ||
| } ins(%out : tensor<1x320xf64>) outs(%out : tensor<1x320xf64>) { | ||
| ^bb0(%element : f64, %outs : f64): | ||
| %bias = arith.constant 5.0 : f64 | ||
| %added = arith.addf %element, %bias : f64 | ||
| linalg.yield %added : f64 | ||
| } -> tensor<1x320xf64> | ||
| func.return %out2 : tensor<1x320xf64> | ||
| } | ||
|
|
||
| func.func @test32_100(%arg0: tensor<1x400xf64>, %arg1: tensor<320x400xf64>) -> tensor<1x320xf64> { | ||
| %init = tensor.empty() : tensor<1x320xf64> | ||
| %out = linalg.matmul_transpose_b { | ||
| lowering_config = #quidditch_snitch.lowering_config< | ||
| l1_tiles = [0, 32, 100], | ||
| l1_tiles_interchange = [2, 0, 1], | ||
| dual_buffer = true | ||
| > | ||
| } | ||
| ins(%arg0, %arg1 : tensor<1x400xf64>, tensor<320x400xf64>) | ||
| outs(%init : tensor<1x320xf64>) -> tensor<1x320xf64> | ||
| %out2 = linalg.generic { | ||
| indexing_maps = [ | ||
| affine_map<(d0, d1) -> (d0, d1)>, | ||
| affine_map<(d0, d1) -> (d0, d1)> | ||
| ], iterator_types = ["parallel", "parallel"] | ||
| } ins(%out : tensor<1x320xf64>) outs(%out : tensor<1x320xf64>) { | ||
| ^bb0(%element : f64, %outs : f64): | ||
| %bias = arith.constant 5.0 : f64 | ||
| %added = arith.addf %element, %bias : f64 | ||
| linalg.yield %added : f64 | ||
| } -> tensor<1x320xf64> | ||
| func.return %out2 : tensor<1x320xf64> | ||
| } | ||
|
|
||
| func.func @test40_100(%arg0: tensor<1x400xf64>, %arg1: tensor<320x400xf64>) -> tensor<1x320xf64> { | ||
| %init = tensor.empty() : tensor<1x320xf64> | ||
| %out = linalg.matmul_transpose_b { | ||
| lowering_config = #quidditch_snitch.lowering_config< | ||
| l1_tiles = [0, 40, 100], | ||
| l1_tiles_interchange = [2, 0, 1], | ||
| dual_buffer = true | ||
| > | ||
| } | ||
| ins(%arg0, %arg1 : tensor<1x400xf64>, tensor<320x400xf64>) | ||
| outs(%init : tensor<1x320xf64>) -> tensor<1x320xf64> | ||
| %out2 = linalg.generic { | ||
| indexing_maps = [ | ||
| affine_map<(d0, d1) -> (d0, d1)>, | ||
| affine_map<(d0, d1) -> (d0, d1)> | ||
| ], iterator_types = ["parallel", "parallel"] | ||
| } ins(%out : tensor<1x320xf64>) outs(%out : tensor<1x320xf64>) { | ||
| ^bb0(%element : f64, %outs : f64): | ||
| %bias = arith.constant 5.0 : f64 | ||
| %added = arith.addf %element, %bias : f64 | ||
| linalg.yield %added : f64 | ||
| } -> tensor<1x320xf64> | ||
| func.return %out2 : tensor<1x320xf64> | ||
| } | ||
| } |
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