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/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
* KIND, either express or implied. See the License for the
* specific language governing permissions and limitations
* under the License.
*/
package org.apache.sysds.runtime.instructions.gpu.context;
import java.util.HashMap;
import org.apache.sysds.runtime.DMLRuntimeException;
import jcuda.driver.CUdevice;
import jcuda.driver.CUdevice_attribute;
import jcuda.driver.CUstream;
/**
* Java Wrapper to specify CUDA execution configuration for launching custom kernels
*/
public class ExecutionConfig {
public int gridDimX;
public int gridDimY = 1;
public int gridDimZ = 1;
public int blockDimX;
public int blockDimY = 1;
public int blockDimZ = 1;
public int sharedMemBytes = 0;
public CUstream stream = null;
private static HashMap<Integer, Integer> maxBlockDimForDevice = new HashMap<>();
/**
* Convenience constructor for setting the number of blocks, number of threads and the
* shared memory size
*
* @param gridDimX Number of blocks on the horizontal axis of the grid (for CUDA Kernel)
* @param blockDimX Number of threads on the horizontal axis of a block (for CUDA Kernel)
* @param sharedMemBytes Amount of Shared memory (for CUDA Kernel)
*/
public ExecutionConfig(int gridDimX, int blockDimX, int sharedMemBytes) {
this.gridDimX = gridDimX;
this.blockDimX = blockDimX;
this.sharedMemBytes = sharedMemBytes;
}
/**
* Convenience constructor for setting the number of blocks, number of threads and the
* shared memory size
*
* @param gridDimX Number of blocks on the horizontal axis of the grid (for CUDA Kernel)
* @param blockDimX Number of threads on the horizontal axis of a block (for CUDA Kernel)
*/
public ExecutionConfig(int gridDimX, int blockDimX) {
this.gridDimX = gridDimX;
this.blockDimX = blockDimX;
}
/**
* Convenience constructor for setting the number of blocks, number of threads and the
* shared memory size
*
* @param gridDimX Number of blocks on the horizontal axis of the grid (for CUDA Kernel)
* @param gridDimY Number of blocks on the vertical axis of the grid (for CUDA Kernel)
* @param blockDimX Number of threads on the horizontal axis of a block (for CUDA Kernel)
* @param blockDimY Number of threads on the vertical axis of a block (for CUDA Kernel)=
*/
public ExecutionConfig(int gridDimX, int gridDimY, int blockDimX, int blockDimY) {
this.gridDimX = gridDimX;
this.gridDimY = gridDimY;
this.blockDimX = blockDimX;
this.blockDimY = blockDimY;
}
/**
* Convenience constructor for setting the number of blocks, number of threads and the
* shared memory size
*
* @param gridDimX Number of blocks on the horizontal axis of the grid (for CUDA Kernel)
* @param gridDimY Number of blocks on the vertical axis of the grid (for CUDA Kernel)
* @param blockDimX Number of threads on the horizontal axis of a block (for CUDA Kernel)
* @param blockDimY Number of threads on the vertical axis of a block (for CUDA Kernel)
* @param sharedMemBytes Amount of Shared memory (for CUDA Kernel)
*/
public ExecutionConfig(int gridDimX, int gridDimY, int blockDimX, int blockDimY, int sharedMemBytes) {
this.gridDimX = gridDimX;
this.gridDimY = gridDimY;
this.blockDimX = blockDimX;
this.blockDimY = blockDimY;
this.sharedMemBytes = sharedMemBytes;
}
/**
* Use this for simple vector operations and use following in the kernel
* <code>
* int index = blockIdx.x * blockDim.x + threadIdx.x
* </code>
* <p>
* This tries to schedule as minimum grids as possible.
*
* @param numCells number of cells
* @return execution configuration
*/
public static ExecutionConfig getConfigForSimpleVectorOperations(int numCells) {
if(numCells == 0)
throw new DMLRuntimeException("Attempting to invoke a kernel with 0 threads");
int deviceNumber = 0;
int blockDimX = getMaxBlockDim(deviceNumber);
int gridDimX = (int) Math.ceil((double) numCells / blockDimX);
return new ExecutionConfig(gridDimX, blockDimX);
}
/**
* Use this for simple vector operations and use following in the kernel
* <code>
* int index = blockIdx.x * blockDim.x + threadIdx.x
* </code>
* <p>
* @param rlen number of rows
* @param clen number of columns
* @return execution configuration
*/
public static ExecutionConfig getConfigForSimpleMatrixOperations(int rlen, int clen) {
return getConfigForSimpleVectorOperations(rlen * clen);
}
/**
* Get the CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X of the given device
*
* @param deviceNumber device number of the given device
* @return The maximum block dimension, in x-direction
*/
private static int getMaxBlockDim(int deviceNumber) {
// return 32;
// TODO: Use JCudaDriver.cuOccupancyMaxPotentialBlockSize to chose the block size that maximizes occupancy
Integer ret = maxBlockDimForDevice.get(deviceNumber);
if (ret == null) {
CUdevice device = new CUdevice();
JCudaKernels.checkResult(jcuda.driver.JCudaDriver.cuDeviceGet(device, deviceNumber));
int maxBlockDimX[] = { 0 };
jcuda.driver.JCudaDriver
.cuDeviceGetAttribute(maxBlockDimX, CUdevice_attribute.CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X, device);
maxBlockDimForDevice.put(deviceNumber, maxBlockDimX[0]);
return maxBlockDimX[0];
}
return ret;
}
@Override
public String toString() {
return "ExecutionConfig{" + "gridDimX=" + gridDimX + ", gridDimY=" + gridDimY + ", gridDimZ=" + gridDimZ
+ ", blockDimX=" + blockDimX + ", blockDimY=" + blockDimY + ", blockDimZ=" + blockDimZ
+ ", sharedMemBytes=" + sharedMemBytes + '}';
}
}