mirror of
https://github.com/sgjzfzzf/triton-tvm-ffi.git
synced 2026-05-02 03:52:11 +08:00
@@ -1,4 +1,6 @@
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#include <cassert>
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#include <cuda.h>
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#include <optional>
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#include <tvm/ffi/extra/cuda/cubin_launcher.h>
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#include <tvm/ffi/function.h>
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@@ -9,32 +11,60 @@
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{% if fn.ctypes is none %}
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#define {{ fn.fnname | upper }}_STUB tvm::ffi::Function::GetGlobalRequired("{{ fn.fullname }}")
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{% else %}
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TVM_FFI_EMBED_CUBIN(triton_{{ fn.fnname }});
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#define {{ fn.fnname | upper}}_STUB(__grid, __stream, __numWarps, __numStages{% for ctype in fn.ctypes %}, {{ "__arg" ~ loop.index0 }}{% endfor %}) do { \
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const tvm::ffi::Map<tvm::ffi::String, tvm::ffi::Any> __meta = { \
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{% for name in fn.signature %}
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{ "{{ name }}", __arg{{ loop.index0 }} }, \
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static const char __cubin[] = "{{ fn.kernel_cstr }}";
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#define __CUDA_CHECK(code) assert((code) == CUDA_SUCCESS)
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static CUfunction __Get{{ fn.fnname }}Kernel() {
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static std::optional<CUfunction> function = std::nullopt;
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if (!function) {
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CUmodule module;
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CUfunction func;
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__CUDA_CHECK(cuModuleLoadData(&module, __cubin));
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__CUDA_CHECK(cuModuleGetFunction(&func, module, "{{ fn.fnname }}"));
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{% if fn.shmem > 49152 %}
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int shared_optin, shared_static;
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__CUDA_CHECK(cuDeviceGetAttribute(&shared_optin, CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_BLOCK_OPTIN, /* TODO: we assume the device id is 0 here, but this may not work on devices with more than one gpu */0));
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if (shared_optin >= 49152) {
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__CUDA_CHECK(cuFuncGetAttribute(&shared_static, CU_FUNC_ATTRIBUTE_SHARED_SIZE_BYTES, func));
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__CUDA_CHECK(cuFuncSetAttribute(func, CU_FUNC_ATTRIBUTE_MAX_DYNAMIC_SHARED_SIZE_BYTES, shared_optin - shared_static));
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}
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{% endif %}
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function = func;
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}
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return *function;
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}
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#define {{ fn.fnname | upper }}_STUB(__grid, __stream, __numWarps, __numStages, __args, __kwargs) do { \
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const char *__signature[] = { "{{ fn.signature | join("\", \"") }}" }; \
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tvm::ffi::Map<tvm::ffi::String, tvm::ffi::Any> __meta = { \
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{% if fn.best_config != none %}
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{% for k, v in fn.best_config.items() %}
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{ "{{ k }}", {{ v }} }, \
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{% endfor %}
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}; \
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static auto __kernel = TVM_FFI_EMBED_CUBIN_GET_KERNEL(triton_{{ fn.fnname }}, "{{ fn.fnname }}"); \
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tvm::ffi::dim3 __gridDim = MakeGridDim(__grid, __meta); \
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tvm::ffi::dim3 __block({% if fn.num_warps != none %}{{ fn.num_warps }}{% else %}__numWarps{% endif %} * 32, 1, 1); \
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void *dummy = nullptr
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{%- for ctype in fn.ctypes -%}
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{%- if ctype == "CUdeviceptr" -%}
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, *__arg{{ loop.index0 }}_ptr=__arg{{ loop.index0 }}.data_ptr()
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{%- endif -%}
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{%- endfor -%}; \
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void *__params[] = {
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{%- for ctype in fn.ctypes -%}
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{%- if ctype != none -%}
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&__arg{{ loop.index0 }}
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{%- if ctype == "CUdeviceptr" -%}
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_ptr
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{%- endif -%},
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{%- endif -%}
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{%- endfor -%}&dummy, &dummy }; \
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TVM_FFI_CHECK_CUBIN_LAUNCHER_CUDA_ERROR(__kernel.Launch(__params, __gridDim, __block, static_cast<tvm::ffi::cuda_api::StreamHandle>(__stream))); \
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{% endif %}
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}; \
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for (size_t __i = 0, __size_args = __args.size(); __i < sizeof(__signature) / sizeof(const char *); ++__i) { \
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if (__i < __size_args) { \
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__meta.Set(__signature[__i], __args[__i]); \
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} else if (auto __val = __kwargs.Get(__signature[__i])) { \
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__meta.Set(__signature[__i], *__val); \
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} \
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} \
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CUfunction __function = __Get{{ fn.fnname }}Kernel(); \
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tvm::ffi::Tuple<int32_t, int32_t, int32_t> __gridDim = MakeGridDim(__grid, __meta); \
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void *dummy = nullptr; \
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{% for ctype in fn.ctypes %}
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{% if ctype != none %}
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{% if ctype == "CUdeviceptr" %}
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void *__arg{{ loop.index0 }} = __args[{{ loop.index0 }}].cast<tvm::ffi::TensorView>().data_ptr(); \
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{% else %}
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{{ ctype }} __arg{{ loop.index0 }} = __args[{{ loop.index0 }}].cast<{{ ctype }}>(); \
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{% endif %}
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{% endif %}
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{% endfor %}
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void *__params[] = { {% for ctype in fn.ctypes %}{% if ctype != none %}&__arg{{ loop.index0 }}, {% endif %}{% endfor %}&dummy, &dummy }; \
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__CUDA_CHECK(cuLaunchKernel(__function, __gridDim.get<0>(), __gridDim.get<1>(), __gridDim.get<2>(), 32 * {{ fn.num_warps }}, 1, 1, {{ fn.shmem }}, reinterpret_cast<CUstream>(__stream), __params, nullptr)); \
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} while (false)
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{% endif %}
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{% endfor %}
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