| /* |
| * 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 static jcuda.driver.JCudaDriver.cuLaunchKernel; |
| import static jcuda.driver.JCudaDriver.cuModuleGetFunction; |
| import static jcuda.driver.JCudaDriver.cuModuleLoadDataEx; |
| |
| import java.io.ByteArrayOutputStream; |
| import java.io.IOException; |
| import java.io.InputStream; |
| import java.util.HashMap; |
| |
| import org.apache.sysds.api.DMLScript; |
| import org.apache.sysds.runtime.DMLRuntimeException; |
| import org.apache.sysds.runtime.io.IOUtilFunctions; |
| import org.apache.sysds.runtime.matrix.data.LibMatrixCUDA; |
| |
| import jcuda.Pointer; |
| import jcuda.driver.CUfunction; |
| import jcuda.driver.CUmodule; |
| import jcuda.driver.CUresult; |
| import jcuda.runtime.JCuda; |
| |
| public class JCudaKernels { |
| |
| private final static String ptxFileName = "/cuda/kernels/SystemDS.ptx"; |
| private HashMap<String, CUfunction> kernels = new HashMap<>(); |
| private CUmodule module; |
| |
| /** |
| * Loads the kernels in the file ptxFileName. Though cubin files are also supported, we will stick with |
| * ptx file as they are target-independent similar to Java's .class files. |
| */ |
| JCudaKernels() { |
| module = new CUmodule(); |
| // Load the kernels specified in the ptxFileName file |
| checkResult(cuModuleLoadDataEx(module, initKernels(ptxFileName), 0, new int[0], Pointer.to(new int[0]))); |
| } |
| |
| /** |
| * Setups the kernel parameters and launches the kernel using cuLaunchKernel API. |
| * This function currently supports two dimensional grid and blocks. |
| * |
| * @param name name of the kernel |
| * @param config execution configuration |
| * @param arguments can be of type Pointer, long, double, float and int |
| */ |
| public void launchKernel(String name, ExecutionConfig config, Object... arguments) { |
| name = name + LibMatrixCUDA.customKernelSuffix; |
| CUfunction function = kernels.get(name); |
| |
| if (function == null) { |
| // caching functions into hashmap reduces the lookup overhead |
| function = new CUfunction(); |
| try { |
| checkResult(cuModuleGetFunction(function, module, name)); |
| } catch(jcuda.CudaException e) { |
| throw new DMLRuntimeException("Error finding the custom kernel:" + name, e); |
| } |
| } |
| |
| // Setup parameters |
| Pointer[] kernelParams = new Pointer[arguments.length]; |
| for (int i = 0; i < arguments.length; i++) { |
| if (arguments[i] == null) { |
| throw new DMLRuntimeException("The argument to the kernel cannot be null."); |
| } else if (arguments[i] instanceof Pointer) { |
| kernelParams[i] = Pointer.to((Pointer) arguments[i]); |
| } else if (arguments[i] instanceof Integer) { |
| kernelParams[i] = Pointer.to(new int[] { (Integer) arguments[i] }); |
| } else if (arguments[i] instanceof Double) { |
| kernelParams[i] = Pointer.to(new double[] { (Double) arguments[i] }); |
| } else if (arguments[i] instanceof Long) { |
| kernelParams[i] = Pointer.to(new long[] { (Long) arguments[i] }); |
| } else if (arguments[i] instanceof Float) { |
| kernelParams[i] = Pointer.to(new float[] { (Float) arguments[i] }); |
| } else { |
| throw new DMLRuntimeException("The argument of type " + arguments[i].getClass() + " is not supported."); |
| } |
| } |
| |
| // Launches the kernel using CUDA's driver API. |
| checkResult(cuLaunchKernel(function, config.gridDimX, config.gridDimY, config.gridDimZ, config.blockDimX, |
| config.blockDimY, config.blockDimZ, config.sharedMemBytes, config.stream, Pointer.to(kernelParams), |
| null)); |
| if(DMLScript.SYNCHRONIZE_GPU) |
| JCuda.cudaDeviceSynchronize(); |
| } |
| |
| public static void checkResult(int cuResult) { |
| if (cuResult != CUresult.CUDA_SUCCESS) { |
| throw new DMLRuntimeException(CUresult.stringFor(cuResult)); |
| } |
| } |
| |
| /** |
| * Reads the ptx file from resource |
| * |
| * @param ptxFileName |
| * @return |
| */ |
| private static Pointer initKernels(String ptxFileName) { |
| ByteArrayOutputStream out = null; |
| try( InputStream in = JCudaKernels.class.getResourceAsStream(ptxFileName) ) { |
| if (in != null) { |
| out = new ByteArrayOutputStream(); |
| byte buffer[] = new byte[8192]; |
| while (true) { |
| int read = in.read(buffer); |
| if (read == -1) |
| break; |
| out.write(buffer, 0, read); |
| } |
| out.write('\0'); |
| out.flush(); |
| return Pointer.to(out.toByteArray()); |
| } else { |
| throw new DMLRuntimeException("The input file " + ptxFileName |
| + " not found. (Hint: Please compile SystemDS using -DenableGPU=true flag. Example: mvn package -DenableGPU=true)."); |
| } |
| } catch (IOException e) { |
| throw new DMLRuntimeException("Could not initialize the kernels", e); |
| } finally { |
| IOUtilFunctions.closeSilently(out); |
| } |
| } |
| } |