[FRONTEND] refactor compiler submodule

.github/workflows/integration-tests.yml

@@ -34,7 +34,6 @@ jobs:
             echo '::set-output name=matrix-optional::["ubuntu-latest"]'
           fi
 
-
   Integration-Tests:
     needs: Runner-Preparation
 
@@ -49,7 +48,7 @@ jobs:
       - name: Checkout
         uses: actions/checkout@v3
         with:
-          submodules: 'true'
+          submodules: "true"
       - name: Set CUDA ENV
         if: ${{(matrix.runner[0] == 'self-hosted') && (matrix.runner[1] == 'V100' || matrix.runner[1] == 'A100' || matrix.runner[1] == 'H100')}}
         run: |

python/setup.py

@@ -353,6 +353,7 @@ def build_extension(self, ext):
         "triton/_C",
         "triton/common",
         "triton/compiler",
+        "triton/compiler/backends",
         "triton/language",
         "triton/language/extra",
         "triton/ops",

python/src/triton.cc

@@ -1685,9 +1685,9 @@ void init_triton_ir(py::module &&m) {
              self.addPass(mlir::triton::createReorderBroadcastPass());
            })
       .def("add_rewrite_tensor_pointer_pass",
-           [](mlir::PassManager &self, int computeCapability) {
-             self.addPass(mlir::triton::createRewriteTensorPointerPass(
-                 computeCapability));
+           [](mlir::PassManager &self, int capability) {
+             self.addPass(
+                 mlir::triton::createRewriteTensorPointerPass(capability));
            })
       .def("add_tritongpu_ws_feasibility_checking_pass",
            [](mlir::PassManager &self, int computeCapability) {
@@ -1761,9 +1761,9 @@ void init_triton_ir(py::module &&m) {
              self.addPass(mlir::createTritonGPUReorderInstructionsPass());
            })
       .def("add_tritongpu_rewrite_tensor_pointer_pass",
-           [](mlir::PassManager &self, int computeCapability) {
-             self.addPass(mlir::createTritonGPURewriteTensorPointerPass(
-                 computeCapability));
+           [](mlir::PassManager &self, int capability) {
+             self.addPass(
+                 mlir::createTritonGPURewriteTensorPointerPass(capability));
            })
       .def("add_tritongpu_decompose_conversions_pass",
            [](mlir::PassManager &self) {

python/test/unit/hopper/test_persistent_warp_specialized_gemm.py

@@ -900,11 +900,12 @@ def process_epilogue(d, bias, w, epilogue):
     num_SMs = torch.cuda.get_device_properties('cuda').multi_processor_count
     if NUM_CTAS > 1:
         device = get_current_device()
-        null_kernel = triton.compile(empty_kernel, signature="i32", constants={"BLOCK_M": 64, "BLOCK_N": 64})
+        src = triton.compiler.ASTSource(fn=empty_kernel, signature="i32", constants={"BLOCK_M": 64, "BLOCK_N": 64})
+        null_kernel = triton.compile(src)
         null_kernel._init_handles()
         max_shared_mem = driver.utils.get_device_properties(device)["max_shared_mem"]
-        num_clusters = driver.utils.cu_occupancy_max_active_clusters(null_kernel.cu_function, max_shared_mem, NUM_CTAS,
-                                                                     1, 1)
+        num_clusters = driver.utils.cu_occupancy_max_active_clusters(null_kernel.function, max_shared_mem, NUM_CTAS, 1,
+                                                                     1)
         num_SMs = num_clusters
 
     def grid(META):

python/test/unit/runtime/test_subproc.py

@@ -1,12 +1,12 @@
 import multiprocessing
 import os
 import shutil
-from collections import namedtuple
 
 import torch
 
 import triton
 import triton.language as tl
+from triton.compiler import ASTSource
 
 tmpdir = ".tmp"
 
@@ -17,32 +17,26 @@ def reset_tmp_dir():
         shutil.rmtree(tmpdir, ignore_errors=True)
 
 
-instance_descriptor = namedtuple("instance_descriptor",
-                                 ["divisible_by_16", "equal_to_1", "ids_of_folded_args", "divisible_by_8"])
-
-
-def compile_fn(config, cc):
+def compile_fn(attrs, capability):
 
     @triton.jit
     def kernel_sub(a, b, o, N: tl.constexpr):
         idx = tl.arange(0, N)
         tl.store(o + idx, tl.load(a + idx) - tl.load(b + idx) * 777)
 
-    triton.compile(
+    src = ASTSource(
         fn=kernel_sub,
-        signature={0: "*fp32", 1: "*fp32", 2: "*fp32"},
-        device=0,
         constants={3: 32},
-        configs=[config],
-        warm_cache_only=True,
-        cc=cc,
+        signature={0: "*fp32", 1: "*fp32", 2: "*fp32"},
+        attrs=attrs,
     )
+    triton.compile(src=src, target=("cuda", capability))
 
 
 def test_compile_in_subproc() -> None:
     major, minor = torch.cuda.get_device_capability(0)
     cc = major * 10 + minor
-    config = instance_descriptor(tuple(range(4)), (), (), ())
+    config = triton.compiler.AttrsDescriptor(tuple(range(4)), (), (), ())
 
     multiprocessing.set_start_method('fork')
     proc = multiprocessing.Process(target=compile_fn, args=(config, cc))
@@ -51,7 +45,7 @@ def test_compile_in_subproc() -> None:
     assert proc.exitcode == 0
 
 
-def compile_fn_dot(config, cc):
+def compile_fn_dot(attrs, capability):
 
     @triton.jit
     def kernel_dot(Z):
@@ -60,24 +54,18 @@ def kernel_dot(Z):
         z = tl.dot(z, z)
         tl.store(Z + offs, z)
 
-    triton.compile(
-        fn=kernel_dot,
-        signature={0: "*fp32"},
-        device=0,
-        configs=[config],
-        warm_cache_only=True,
-        cc=cc,
-    )
+    src = ASTSource(fn=kernel_dot, signature={0: "*fp32"}, attrs=attrs, constants=dict())
+    triton.compile(src=src, target=("cuda", capability))
 
 
 def test_compile_in_forked_subproc() -> None:
     reset_tmp_dir()
     major, minor = torch.cuda.get_device_capability(0)
-    cc = major * 10 + minor
-    config = instance_descriptor(tuple(range(1)), (), (), ())
+    capability = major * 10 + minor
+    config = triton.compiler.AttrsDescriptor(tuple(range(1)), (), (), ())
 
     assert multiprocessing.get_start_method() == 'fork'
-    proc = multiprocessing.Process(target=compile_fn_dot, args=(config, cc))
+    proc = multiprocessing.Process(target=compile_fn_dot, args=(config, capability))
     proc.start()
     proc.join()
     assert proc.exitcode == 0

python/test/unit/tools/test_aot.py

@@ -446,7 +446,7 @@ def test_ttgir_to_ptx():
         kernel_path = os.path.join(tmp_dir, "empty_kernel.ttgir")
         with open(kernel_path, "w") as fp:
             fp.write(src)
-        k = triton.compile(kernel_path, cc=80)
+        k = triton.compile(kernel_path, target=("cuda", 80))
         ptx = k.asm["ptx"]
         assert ".target sm_80" in ptx
         assert ".address_size 64" in ptx

python/triton/__init__.py

@@ -21,6 +21,7 @@
 
 from . import language
 from . import testing
+from . import tools
 
 __all__ = [
     "autotune",

python/triton/compiler/__init__.py

@@ -1,8 +1,7 @@
-from .compiler import (CompiledKernel, compile, get_arch_default_num_stages, get_arch_default_num_warps,
-                       instance_descriptor)
+from .compiler import (CompiledKernel, ASTSource, compile, AttrsDescriptor)
 from .errors import CompilationError
 
 __all__ = [
-    "compile", "instance_descriptor", "CompiledKernel", "CompilationError", "get_arch_default_num_warps",
+    "compile", "ASTSource", "AttrsDescriptor", "CompiledKernel", "CompilationError", "get_arch_default_num_warps",
     "get_arch_default_num_stages"
 ]