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211 lines
5.2 KiB
Plaintext
211 lines
5.2 KiB
Plaintext
1 year ago
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/*
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* spGPU - Sparse matrices on GPU library.
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*
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* Copyright (C) 2010 - 2014
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* Salvatore Filippone - University of Rome Tor Vergata
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* Davide Barbieri - University of Rome Tor Vergata
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*
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* This program is free software; you can redistribute it and/or
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* modify it under the terms of the GNU General Public License
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* version 3 as published by the Free Software Foundation.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*/
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#define PRE_CONCAT(A, B) A ## B
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#define CONCAT(A, B) PRE_CONCAT(A, B)
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#undef GEN_SPGPU_FUNC_NAME
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#define GEN_SPGPU_FUNC_NAME(x) CONCAT(CONCAT(spgpu,x),axy)
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#define GEN_SPGPU_MFUNC_NAME(x) CONCAT(CONCAT(spgpu,x),maxy)
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#define GEN_SPGPU_FUNC_NAME_2(x) CONCAT(CONCAT(spgpu,x),axypbz)
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#define GEN_SPGPU_MFUNC_NAME_2(x) CONCAT(CONCAT(spgpu,x),maxypbz)
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#define GEN_SPGPU_SCAL_NAME(x) CONCAT(CONCAT(spgpu,x),scal)
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#define BLOCK_SIZE 256
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// Define:
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//#define VALUE_TYPE
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//#define TYPE_SYMBOL
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#include "mathbase.cuh"
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__global__ void
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CONCAT(GEN_SPGPU_FUNC_NAME(TYPE_SYMBOL),_kern)
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(VALUE_TYPE *z, int n, VALUE_TYPE alpha, VALUE_TYPE* x, VALUE_TYPE* y)
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{
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int id = threadIdx.x + BLOCK_SIZE*blockIdx.x;
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if (id < n)
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{
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// Since z, x and y are accessed with the same offset by the same thread,
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// and the write to z follows the x and y reads, x, y and z can share the same base address (in-place computing).
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z[id] = CONCAT(VALUE_TYPE, _mul)(alpha, CONCAT(VALUE_TYPE, _mul)(x[id], y[id]));
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}
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}
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void
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CONCAT(GEN_SPGPU_FUNC_NAME(TYPE_SYMBOL),_)
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(spgpuHandle_t handle, VALUE_TYPE *z, int n, VALUE_TYPE alpha, VALUE_TYPE* x, VALUE_TYPE* y)
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{
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int msize = (n+BLOCK_SIZE-1)/BLOCK_SIZE;
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dim3 block(BLOCK_SIZE);
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dim3 grid(msize);
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CONCAT(GEN_SPGPU_FUNC_NAME(TYPE_SYMBOL),_kern)<<<grid, block, 0, handle->currentStream>>>(z, n, alpha, x, y);
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}
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void
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GEN_SPGPU_FUNC_NAME(TYPE_SYMBOL)
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(spgpuHandle_t handle,
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__device VALUE_TYPE *z,
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int n,
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VALUE_TYPE alpha,
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__device VALUE_TYPE *x,
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__device VALUE_TYPE *y)
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{
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int maxNForACall = max(handle->maxGridSizeX, BLOCK_SIZE*handle->maxGridSizeX);
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while (n > maxNForACall) //managing large vectors
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{
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CONCAT(GEN_SPGPU_FUNC_NAME(TYPE_SYMBOL),_)
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(handle, z, maxNForACall, alpha, x, y);
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x = x + maxNForACall;
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y = y + maxNForACall;
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z = z + maxNForACall;
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n -= maxNForACall;
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}
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CONCAT(GEN_SPGPU_FUNC_NAME(TYPE_SYMBOL),_) (handle, z, n, alpha, x, y);
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cudaCheckError("CUDA error on axy");
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}
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void
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GEN_SPGPU_MFUNC_NAME(TYPE_SYMBOL)
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(spgpuHandle_t handle,
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__device VALUE_TYPE *z,
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int n,
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VALUE_TYPE alpha,
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__device VALUE_TYPE* x,
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__device VALUE_TYPE *y,
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int count,
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int pitch)
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{
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for (int i=0; i<count; i++)
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{
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GEN_SPGPU_FUNC_NAME(TYPE_SYMBOL)(handle, z, n, alpha, x, y);
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x += pitch;
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y += pitch;
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z += pitch;
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}
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}
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__global__ void
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CONCAT(GEN_SPGPU_FUNC_NAME_2(TYPE_SYMBOL),_kern)
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(VALUE_TYPE *w, int n, VALUE_TYPE beta, VALUE_TYPE* z, VALUE_TYPE alpha, VALUE_TYPE* x, VALUE_TYPE* y)
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{
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int id = threadIdx.x + BLOCK_SIZE*blockIdx.x;
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if (id < n)
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{
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// Since w, x and y and z are accessed with the same offset by the same thread,
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// and the write to z follows the x, y and z reads, x, y, z and w can share the same base address (in-place computing).
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w[id] = CONCAT(VALUE_TYPE, _fma) (
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alpha,
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CONCAT(VALUE_TYPE, _mul)(x[id],y[id]),
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CONCAT(VALUE_TYPE, _mul)(beta,z[id]));
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}
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}
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void
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CONCAT(GEN_SPGPU_FUNC_NAME_2(TYPE_SYMBOL),_)
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(spgpuHandle_t handle, VALUE_TYPE *w, int n, VALUE_TYPE beta, VALUE_TYPE* z, VALUE_TYPE alpha, VALUE_TYPE* x, VALUE_TYPE* y)
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{
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int msize = (n+BLOCK_SIZE-1)/BLOCK_SIZE;
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dim3 block(BLOCK_SIZE);
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dim3 grid(msize);
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CONCAT(GEN_SPGPU_FUNC_NAME_2(TYPE_SYMBOL),_kern)
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<<<grid, block, 0, handle->currentStream>>>(w, n, beta, z, alpha, x, y);
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}
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void
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GEN_SPGPU_FUNC_NAME_2(TYPE_SYMBOL)
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(spgpuHandle_t handle,
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__device VALUE_TYPE *w,
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int n,
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VALUE_TYPE beta,
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__device VALUE_TYPE *z,
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VALUE_TYPE alpha,
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__device VALUE_TYPE* x,
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__device VALUE_TYPE *y
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)
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{
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if (CONCAT(VALUE_TYPE, _isZero(alpha)))
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{
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GEN_SPGPU_SCAL_NAME(TYPE_SYMBOL)
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(handle, w, n, beta, z);
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}
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else if (CONCAT(VALUE_TYPE, _isZero(beta))) {
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GEN_SPGPU_FUNC_NAME(TYPE_SYMBOL)
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(handle, w, n, alpha, x, y);
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}
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else {
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int maxNForACall = max(handle->maxGridSizeX, BLOCK_SIZE*handle->maxGridSizeX);
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while (n > maxNForACall) //managing large vectors
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{
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CONCAT(GEN_SPGPU_FUNC_NAME_2(TYPE_SYMBOL),_)
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(handle, w, maxNForACall, beta, z, alpha, x, y);
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x = x + maxNForACall;
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y = y + maxNForACall;
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z = z + maxNForACall;
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w = w + maxNForACall;
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n -= maxNForACall;
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}
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CONCAT(GEN_SPGPU_FUNC_NAME_2(TYPE_SYMBOL),_)
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(handle, w, n, beta, z, alpha, x, y);
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}
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cudaCheckError("CUDA error on axypbz");
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}
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void
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GEN_SPGPU_MFUNC_NAME_2(TYPE_SYMBOL)
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(spgpuHandle_t handle,
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__device VALUE_TYPE *w,
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int n,
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VALUE_TYPE beta,
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__device VALUE_TYPE *z,
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VALUE_TYPE alpha,
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__device VALUE_TYPE* x,
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__device VALUE_TYPE *y,
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int count,
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int pitch)
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{
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for (int i=0; i<count; i++)
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{
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GEN_SPGPU_FUNC_NAME_2(TYPE_SYMBOL)(handle, w, n, beta, z, alpha, x, y);
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x += pitch;
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y += pitch;
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z += pitch;
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w += pitch;
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}
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}
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