| #blocked = #triton_gpu.blocked<{sizePerThread = [2], threadsPerWarp = [32], warpsPerCTA = [4], order = [0], CTAsPerCGA = [1], CTASplitNum = [1], CTAOrder = [0]}> | |
| module attributes {"triton_gpu.compute-capability" = 89 : i32, "triton_gpu.num-ctas" = 1 : i32, "triton_gpu.num-warps" = 4 : i32, "triton_gpu.threads-per-warp" = 32 : i32} { | |
| tt.func public @triton__0d1de(%arg0: !tt.ptr<i64, 1> {tt.divisibility = 16 : i32}, %arg1: i32 {tt.divisibility = 16 : i32, tt.max_divisibility = 16 : i32}) attributes {noinline = false} { | |
| %cst = arith.constant dense<512> : tensor<256xi32, #blocked> | |
| %c256_i32 = arith.constant 256 : i32 | |
| %0 = tt.get_program_id x : i32 | |
| %1 = arith.muli %0, %c256_i32 : i32 | |
| %2 = tt.make_range {end = 256 : i32, start = 0 : i32} : tensor<256xi32, #blocked> | |
| %3 = tt.splat %1 : (i32) -> tensor<256xi32, #blocked> | |
| %4 = arith.addi %3, %2 : tensor<256xi32, #blocked> | |
| %5 = arith.cmpi slt, %4, %cst : tensor<256xi32, #blocked> | |
| %6 = tt.splat %arg0 : (!tt.ptr<i64, 1>) -> tensor<256x!tt.ptr<i64, 1>, #blocked> | |
| %7 = tt.addptr %6, %4 : tensor<256x!tt.ptr<i64, 1>, #blocked>, tensor<256xi32, #blocked> | |
| %8 = arith.extsi %4 : tensor<256xi32, #blocked> to tensor<256xi64, #blocked> | |
| tt.store %7, %8, %5 {cache = 1 : i32, evict = 1 : i32} : tensor<256xi64, #blocked> | |
| tt.return | |
| } | |
| } | |