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- # StarPU --- Runtime system for heterogeneous multicore architectures.
- #
- # Copyright (C) 2020 Université de Bordeaux, CNRS (LaBRI UMR 5800), Inria
- #
- # StarPU is free software; you can redistribute it and/or modify
- # it under the terms of the GNU Lesser General Public License as published by
- # the Free Software Foundation; either version 2.1 of the License, or (at
- # your option) any later version.
- #
- # StarPU is distributed in the hope that it will be useful, but
- # WITHOUT ANY WARRANTY; without even the implied warranty of
- # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
- #
- # See the GNU Lesser General Public License in COPYING.LGPL for more details.
- #
- using StarPU
- using LinearAlgebra.BLAS
- @target STARPU_CPU+STARPU_CUDA
- @codelet function gemm(A :: Matrix{Float32}, B :: Matrix{Float32}, C :: Matrix{Float32}, alpha :: Float32, beta :: Float32) :: Nothing
- M :: Int32 = height(A)
- N :: Int32 = width(B)
- K :: Int32 = width(A)
- lda :: Int32 = ld(A)
- ldb :: Int32 = ld(B)
- ldc :: Int32 = ld(C)
- STARPU_SGEMM("N", "N", M, N, K, alpha, A, lda, B, ldb, beta, C, ldc)
- return
- end
- function multiply_with_starpu(A :: Matrix{Float32}, B :: Matrix{Float32}, C :: Matrix{Float32}, alpha :: Float32, beta :: Float32, nslicesx, nslicesy)
- scale= 3
- tmin=0
- hA,hB,hC = starpu_data_register(A, B, C)
- tmin=0
- perfmodel = starpu_perfmodel(
- perf_type = starpu_perfmodel_type(STARPU_HISTORY_BASED),
- symbol = "gemm"
- )
- cl = starpu_codelet(
- cpu_func = "gemm",
- cuda_func = "",
- modes =[STARPU_R,STARPU_R,STARPU_RW],
- perfmodel = perfmodel,
- )
- task = starpu_task(cl = cl, handles =[hA,hB,hC], cl_arg = (alpha,beta), callback = nothing,
- callback_arg = nothing, tag = nothing, tag_only = nothing,
- sequential_consistency = true,
- detach = 1, color = nothing, where = nothing)
- for i in (1 : 10 )
- t=time_ns()
- starpu_task_submit(Ref(task.c_task))
- #starpu_task_submit(task)
- starpu_task_wait_for_all()
- t=time_ns()-t
- if (tmin==0 || tmin>t)
- tmin=t
- end
- end
- starpu_data_unregister(hA)
- starpu_data_unregister(hB)
- starpu_data_unregister(hC)
- return tmin
- end
- function approximately_equals(
- A :: Matrix{Cfloat},
- B :: Matrix{Cfloat},
- eps = 1e-2
- )
- (height, width) = size(A)
- for j in (1 : width)
- for i in (1 : height)
- if (abs(A[i,j] - B[i,j]) > eps * max(abs(B[i,j]), abs(A[i,j])))
- println("A[$i,$j] : $(A[i,j]), B[$i,$j] : $(B[i,j])")
- return false
- end
- end
- end
- return true
- end
- function check(expected, A, B, C, alpha, beta)
- for i in 1 : 10
- gemm!('N', 'N', alpha, A, B, beta, expected)
- end
- height,width = size(C)
- for i in 1:height
- for j in 1:width
- got = C[i, j]
- exp = expected[i, j]
- err = abs(exp - got) / exp
- if err > 0.0001
- error("[$i] -> $got != $exp (err $err)")
- end
- end
- end
- end
- function compute_times(io,start_dim, step_dim, stop_dim, nslicesx, nslicesy)
- for dim in (start_dim : step_dim : stop_dim)
- A = Array(rand(Cfloat, dim, dim))
- B = Array(rand(Cfloat, dim, dim))
- C = zeros(Float32, dim, dim)
- C_ref = copy(C)
- starpu_memory_pin(A)
- starpu_memory_pin(B)
- starpu_memory_pin(C)
- alpha = 4.0f0
- beta = 2.0f0
- mt = multiply_with_starpu(A, B, C, alpha, beta, nslicesx, nslicesy)
- gflop = 2 * dim * dim * dim * 1.e-9
- gflops = gflop / (mt * 1.e-9)
- size=dim*dim*dim*4*3/1024/1024
- println(io,"$dim $gflops")
- println("$dim $gflops")
- starpu_memory_unpin(A)
- starpu_memory_unpin(B)
- starpu_memory_unpin(C)
- #check(C_ref, A, B, C, alpha, beta)
- end
- end
- if size(ARGS, 1) < 1
- filename="x.dat"
- else
- filename=ARGS[1]
- end
- starpu_init()
- starpu_cublas_init()
- io=open(filename,"w")
- compute_times(io,64,512,4096,1,1)
- close(io)
- starpu_shutdown()
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