gaspersic/triton
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity
768 Commits 14 Branches 9 Tags
keren/v100-perf-regression
Commit Graph

114 Commits

Author SHA1 Message Date
Shintaro Iwasaki
3c635449e5 [Triton] Support math and libdevice ops (#91) 
This PR adds basic math ops by using `MathDialect` and `libdevice` ops by using `extern_elementwise`. This is needed to compile some tutorial code (e.g., `softmax`). This PR implements only interface till PTX (so from frontend to TritonGPU-MLIR) 
- Currently till TritonGPU. It cannot be lowered to PTX now.
- No special optimizations (e.g., constant folding etc) are applied.
  - 14.x does not define folders for many operators for math ops, but 15.x seems to increase its coverage: https://github.com/llvm/llvm-project/blob/llvmorg-15.0.0-rc3/mlir/include/mlir/Dialect/Math/IR/MathOps.td
  - No constant folding etc for `libdevice` ops.

```py
import triton
import triton.language as tl
import sys

@triton.jit
def add_kernel(
    x_ptr,
    y_ptr,
    BLOCK_SIZE: tl.constexpr,
):
    offsets = tl.arange(0, BLOCK_SIZE)
    x = tl.load(x_ptr + offsets)
    x = tl.sin(x)
    output = tl.libdevice.sin(x)
    output = tl.libdevice.fdiv_rn(output, output)
    output = tl.libdevice.fmaf_rd(output, output, output)
    tl.store(y_ptr + offsets, output)


if __name__ == "__main__" and len(sys.argv) >= 2:
    signature = "*fp32,*fp32"
    constants = {'BLOCK_SIZE': 1024}
    output = triton.compile(add_kernel, signature, device=0, constants=constants, output="ttgir")
    print(output)
```
->
```llvm
#blocked = #triton_gpu.blocked<{sizePerThread = [1], threadsPerWarp = [32], warpsPerCTA = [4], order = [0]}>
module attributes {"triton_gpu.num-warps" = 4 : i32} {
  func @add_kernel__Pfp32_Pfp32__2c1024(%arg0: !tt.ptr<f32>, %arg1: !tt.ptr<f32>) {
    %0 = tt.make_range {end = 1024 : i32, start = 0 : i32} : tensor<1024xi32, #blocked>
    %1 = tt.splat %arg0 : (!tt.ptr<f32>) -> tensor<1024x!tt.ptr<f32>, #blocked>
    %2 = tt.getelementptr %1, %0 : tensor<1024x!tt.ptr<f32>, #blocked>
    %3 = tt.load %2 {cache = 1 : i32, evict = 1 : i32, isVolatile = false} : tensor<1024xf32, #blocked>
    %4 = math.sin %3 : tensor<1024xf32, #blocked>
    %5 = tt.ext_elemwise %4 {libname = "libdevice", libpath = "/home/siwasaki/triton/python/triton/language/libdevice.10.bc", symbol = "__nv_sinf"} : tensor<1024xf32, #blocked> -> tensor<1024xf32, #blocked>
    %6 = tt.ext_elemwise %5, %5 {libname = "libdevice", libpath = "/home/siwasaki/triton/python/triton/language/libdevice.10.bc", symbol = "__nv_fdiv_rn"} : tensor<1024xf32, #blocked>, tensor<1024xf32, #blocked> -> tensor<1024xf32, #blocked>
    %7 = tt.ext_elemwise %6, %6, %6 {libname = "libdevice", libpath = "/home/siwasaki/triton/python/triton/language/libdevice.10.bc", symbol = "__nv_fmaf_rd"} : tensor<1024xf32, #blocked>, tensor<1024xf32, #blocked>, tensor<1024xf32, #blocked> -> tensor<1024xf32, #blocked>
    %8 = tt.splat %arg1 : (!tt.ptr<f32>) -> tensor<1024x!tt.ptr<f32>, #blocked>
    %9 = tt.getelementptr %8, %0 : tensor<1024x!tt.ptr<f32>, #blocked>
    tt.store %9, %7 : tensor<1024xf32, #blocked>
    return
  }
}
```
 2022-09-01 16:34:27 -07:00
Shintaro Iwasaki
d01353de07 [CI] add assert-enabled MLIR option (#78) 
This deprecates the use of release-build LLVM hosted by the LLVM project, which makes debugging harder for developers.

This PR implements the following solution:
1. Create LLVM release tarballs with assert enabled on our own (using Docker)
2. Host them in our own GitHub repositories
3. Use our LLVM for CI and/or development if `TRITON_USE_ASSERT_ENABLED_LLVM=1` is set.
 2022-08-31 18:55:32 -07:00
goostavz
bedbf221c0 [BACKEND] Support optional mask in TritonGPUToLLVM (#80) 
Co-authored-by: gzhu <gzhu@nvidia.com>
 2022-08-24 17:51:37 -07:00
Yan Chunwei
1b513c9866 [BACKEND] Refactoring codegen for LoadOp with PTXFormat (#77) 
This PR does following things:

Enhance the PTXFormat by
Introducing PTXBuilder to enable multiple instructions in a single asm program
override PTXInstr's operator() method to enable instr(opr0, opr1) style of setting operands for an instruction
Refactor the PTX code used in LoadOpConversion with PTXFormat

Authored-by: goostavz <gzhu@nvidia.com>
 2022-08-23 15:51:13 -07:00
goostavz
de2dd04c8a [BACKEND] two minor bugfix on StoreOpLowering and kernel launch & support optional other in LoadOpLowering (#69) 
* [BACKEND] two minor bugfix on StoreOpLowering and kernel launch & support optional other in LoadOpLowering

* Clean code

Co-authored-by: goostavz <gzhu@nvidia.com>
Co-authored-by: Yan Chunwei <yanchunwei@outlook.com>
 2022-08-22 21:47:09 -07:00
Yan Chunwei
10ba51c3bb [FRONTEND] add python e2e launch empty kernel test (#68) 2022-08-19 10:46:01 -07:00
Philippe Tillet
192be76b3c [OPTIMIZER] Rewrite patterns for layout conversions (#64) 2022-08-18 12:49:37 -07:00
goostavz
fc58250a06 [BACKEND] Add backend support of arith::AddIOp, arith::AddFOp, GetProgramIdOp & GEPOp and bugfix for SplatOp, StoreOp, FuncOp (#60) 
Add backend support of arith::AddIOp, arith::AddFOp, GetProgramIdOp, GEPOp and bugfix for SplatOp, StoreOp, FuncOp

Co-authored-by: gzhu <gzhu@nvidia.com>
 2022-08-18 20:46:45 +08:00
Yan Chunwei
b1673caaf6 [FRONTEND] Expose end-to-end compile to python frontend (#58) 2022-08-17 10:42:48 -07:00
Yan Chunwei
95bbac41e7 [BACKEND] Add LLVM-translation for store and splat ops (#47) 2022-08-15 00:46:37 -07:00
goostavz
993ba7035a [BACKEND] Codegen bringup, index calculation of blocked_layout & support of LoadOp, BroadcastOp, ViewOp & MakeRangeOp (#38) 
Co-authored-by: gzhu <gzhu@nvidia.com>
 2022-08-14 19:58:59 -07:00
Yan Chunwei
83ef74f248 [BACKEND] Extracting numWarps from tritonGPU module (#39) 2022-08-08 09:40:20 -07:00
Yan Chunwei
920723cf3d [BACKEND] add triton-translate to translate mlir to llvmir or PTX code (#37) 2022-08-07 22:34:36 -07:00
Yan Chunwei
b988bae813 Init TritonGPU to LLVM dialect conversion (#32) 
* add toLLVM pass

* update num-warps setting in mlir
 2022-08-04 10:15:45 +08:00