如何在RStudio / R中使用AMD GPU进行处理？

install.packages("OpenCL") # OpenCL R软件包
install.packages("Rcpp") # R与C++的接口包
install.packages("RcppArmadillo") # 用于线性代数计算的RcppArmadillo包

library(OpenCL)
oclPlatforms()

library(OpenCL)
library(Rcpp)
library(RcppArmadillo)

context <- clCreateContext()

devices <- clGetDeviceIDs(context)

device <- devices[[1]] # 选择第一个设备

queue <- clCreateCommandQueue(context, device)

sourceCode <- "kernel void square(global float* input, global float* output) { int i = get_global_id(0); output[i] = input[i] * input[i]; }"
program <- clCreateProgramWithSource(context, sourceCode)

clBuildProgram(program, device)

kernel <- clCreateKernel(program, "square")

inputBuffer <- clCreateBuffer(context, CL_MEM_READ_ONLY, size = n * sizeof(cl_float), host_ptr = input)
outputBuffer <- clCreateBuffer(context, CL_MEM_WRITE_ONLY, size = n * sizeof(cl_float))

clSetKernelArg(kernel, 0, inputBuffer)
clSetKernelArg(kernel, 1, outputBuffer)

clEnqueueWriteBuffer(queue, inputBuffer, CL_TRUE, 0, size = n * sizeof(cl_float), host_ptr = input)

globalSize <- c(n)
localSize <- NULL
clEnqueueNDRangeKernel(queue, kernel, global_work_size = globalSize, local_work_size = localSize)

output <- clEnqueueReadBuffer(queue, outputBuffer, CL_TRUE, 0, size = n * sizeof(cl_float))