a0615d020a
This commit is part of the migration of towards the new STEA syntax/design. In particular, this commit includes the following changes:
* Renaming compiler-internal functions/methods:
* `SparseTensorEncodingAttr::{getDimLevelType => getLvlTypes}`
* `Merger::{getDimLevelType => getLvlType}` (for consistency)
* `sparse_tensor::{getDimLevelType => buildLevelType}` (to help reduce confusion vs actual getter methods)
* Renaming external facets to match:
* the STEA parser and printer
* the C and Python bindings
* PyTACO
However, the actual renaming of the `DimLevelType` itself (along with all the "dlt" names) will be handled in a separate commit.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D150330
104 lines
3.4 KiB
MLIR
104 lines
3.4 KiB
MLIR
// DEFINE: %{option} = enable-runtime-library=true
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// DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
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// DEFINE: %{run} = TENSOR0="%mlir_src_dir/test/Integration/data/test_symmetric.mtx" \
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// DEFINE: mlir-cpu-runner \
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// DEFINE: -e entry -entry-point-result=void \
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// DEFINE: -shared-libs=%mlir_c_runner_utils | \
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// DEFINE: FileCheck %s
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//
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// RUN: %{compile} | %{run}
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//
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// Do the same run, but now with direct IR generation.
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// REDEFINE: %{option} = enable-runtime-library=false
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// RUN: %{compile} | %{run}
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//
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// Do the same run, but now with direct IR generation and vectorization.
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// REDEFINE: %{option} = "enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true"
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// RUN: %{compile} | %{run}
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// Do the same run, but now with direct IR generation and, if available, VLA
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// vectorization.
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// REDEFINE: %{option} = "enable-runtime-library=false vl=4 enable-arm-sve=%ENABLE_VLA"
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// REDEFINE: %{run} = TENSOR0="%mlir_src_dir/test/Integration/data/test_symmetric.mtx" \
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// REDEFINE: %lli_host_or_aarch64_cmd \
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// REDEFINE: --entry-function=entry_lli \
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// REDEFINE: --extra-module=%S/Inputs/main_for_lli.ll \
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// REDEFINE: %VLA_ARCH_ATTR_OPTIONS \
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// REDEFINE: --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext | \
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// REDEFINE: FileCheck %s
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// RUN: %{compile} | mlir-translate -mlir-to-llvmir | %{run}
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// TODO: The test currently only operates on the triangular part of the
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// symmetric matrix.
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!Filename = !llvm.ptr<i8>
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#SparseMatrix = #sparse_tensor.encoding<{
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lvlTypes = [ "compressed", "compressed" ]
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}>
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#trait_sum_reduce = {
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indexing_maps = [
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affine_map<(i,j) -> (i,j)>, // A
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affine_map<(i,j) -> ()> // x (out)
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],
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iterator_types = ["reduction", "reduction"],
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doc = "x += A(i,j)"
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}
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//
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// Integration test that lowers a kernel annotated as sparse to
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// actual sparse code, initializes a matching sparse storage scheme
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// from file, and runs the resulting code with the JIT compiler.
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//
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module {
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//
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// A kernel that sum-reduces a matrix to a single scalar.
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//
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func.func @kernel_sum_reduce(%arga: tensor<?x?xf64, #SparseMatrix>,
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%argx: tensor<f64>) -> tensor<f64> {
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%0 = linalg.generic #trait_sum_reduce
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ins(%arga: tensor<?x?xf64, #SparseMatrix>)
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outs(%argx: tensor<f64>) {
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^bb(%a: f64, %x: f64):
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%0 = arith.addf %x, %a : f64
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linalg.yield %0 : f64
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} -> tensor<f64>
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return %0 : tensor<f64>
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}
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func.func private @getTensorFilename(index) -> (!Filename)
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//
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// Main driver that reads matrix from file and calls the sparse kernel.
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//
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func.func @entry() {
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%d0 = arith.constant 0.0 : f64
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%c0 = arith.constant 0 : index
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// Setup memory for a single reduction scalar,
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// initialized to zero.
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%x = tensor.from_elements %d0 : tensor<f64>
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// Read the sparse matrix from file, construct sparse storage.
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%fileName = call @getTensorFilename(%c0) : (index) -> (!Filename)
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%a = sparse_tensor.new %fileName : !Filename to tensor<?x?xf64, #SparseMatrix>
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// Call the kernel.
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%0 = call @kernel_sum_reduce(%a, %x)
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: (tensor<?x?xf64, #SparseMatrix>, tensor<f64>) -> tensor<f64>
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// Print the result for verification.
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//
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// CHECK: 24.1
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//
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%v = tensor.extract %0[] : tensor<f64>
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vector.print %v : f64
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// Release the resources.
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bufferization.dealloc_tensor %a : tensor<?x?xf64, #SparseMatrix>
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return
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}
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}
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