我是OpenCL的新手。有人知道如何通过OpenCL读取文本文件吗？因为我希望能够读取文件并将内容拆分为某些数组。 例如，我有txt文件包含： 1010101 1 1010111 。我想将1010101作为数组a，将1010111作为数组b。在这里，我们看到一个标签/空格，它有一个标签分隔符，带有＆＃34; 1＆＃34;，所以我需要用分隔符＆＃34; \ t1＆＃34;同样。
这是我的主要代码：
for (int i = 0; i < N; i++) {
System.out.println("perturb node: "+i);
cs=calcDistanceCs();//ok
System.out.println("csTemp: "+Arrays.toString(cs));
//System.out.println("csTemp: "+cs);
for (int j = 0; j < N; j++) {
if (j!=i) {
System.out.println("target node: "+j);
nTarget=j;
rs=calcDistanceRs();
System.out.println("rsTemp: "+Arrays.toString(rs));
//System.out.println("rsTemp: "+rs);
eff=dtmp/numofRStates;
System.out.println("Effectiveness "+eff);
//print-out result
pw.println(i+"\t"+eff+"\t"+j);
// flush the writer
pw.flush();
}
}
}
Pointer srcA = Pointer.to(cs);
Pointer srcB = Pointer.to(rs);
//Pointer dst = Pointer.to(resultArr);
// The platform, device type and device number
final int platformIndex = 0;
final long deviceType = CL_DEVICE_TYPE_ALL;
final int deviceIndex = 0;
// Enable exceptions and subsequently omit error checks in this sample
CL.setExceptionsEnabled(true);
// Obtain the number of platforms
int numPlatformsArray[] = new int[1];
clGetPlatformIDs(0, null, numPlatformsArray);
int numPlatforms = numPlatformsArray[0];
//obtain a platform id
System.out.println("Obtaining platform..."); //running, muncul
cl_platform_id platforms[] = new cl_platform_id[numPlatforms];
clGetPlatformIDs(platforms.length, platforms, null);
cl_platform_id platform = platforms[platformIndex];
System.out.println("Platform id: "+platform); //uda langsung ke string tanpa harus diconvert
//Initialize the context properties
cl_context_properties contextProperties = new cl_context_properties();
contextProperties.addProperty(CL_CONTEXT_PLATFORM, platform);
// Obtain the number of devices for the platform
int numDevicesArray[] = new int[1];
clGetDeviceIDs(platform, deviceType, 0, null, numDevicesArray);
int numDevices = numDevicesArray[0];
// Obtain a device ID
cl_device_id devices[] = new cl_device_id[numDevices];
clGetDeviceIDs(platform, deviceType, numDevices, devices, null);
cl_device_id device = devices[deviceIndex];
// Create a context for the selected device
cl_context context = clCreateContext(contextProperties, 1, new cl_device_id[]{device},null, null, null);
//create an opencl context on a gpu device
//cl_context context=clCreateContextFromType(contextProperties,CL_DEVICE_TYPE_GPU,null,null,null);
if (context==null) {
/*if no context for a gpu device could be created,
try to create one for a cpu device
*/
System.out.println("Cannot create GPU context...");
context=clCreateContextFromType(contextProperties, CL_DEVICE_TYPE_CPU, null, null, null);
if (context==null) {
System.out.println("Unable to create a context");
return;
}else{
System.out.println("Successfully created CPU context ^^");
}
}else{
System.out.println("Successfully created GPU context...");
}
// Create a command-queue for the selected device
cl_command_queue commandQueue = clCreateCommandQueue(context, device, 0, null);
// Allocate the memory objects for the input- and output data
cl_mem memObjects[] = new cl_mem[2];
memObjects[0] = clCreateBuffer(context,
CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR,
Sizeof.cl_char * N, srcA, null);
memObjects[1] = clCreateBuffer(context,
CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR,
Sizeof.cl_char * N, srcB, null);
/* memObjects[2] = clCreateBuffer(context,
CL_MEM_READ_WRITE,
Sizeof.cl_float * N, null, null);*/
// Create the program from the source code
System.out.println("Reading file from kernels...");
String programSource=readFile("kernel_/CalEff.cl"); //membaca file dari luar folder src--sukses ^^
//create the program from the source code
cl_program program=clCreateProgramWithSource(context,1,new String[]{programSource},null,null);
// Build the program
clBuildProgram(program, 0, null, null, null, null);
// Create the kernel
cl_kernel kernel = clCreateKernel(program, "Effectiveness", null); //nama procedure yg dipanggil di kernel/opencl
// Set the arguments for the kernel -->kernel, arg index,long arg size, pointer
clSetKernelArg(kernel, 0, Sizeof.cl_mem, Pointer.to(memObjects[0]));//jumlahnya ada 3 cz yg dideklarasi jg ada3
clSetKernelArg(kernel, 1, Sizeof.cl_mem, Pointer.to(memObjects[1]));
clSetKernelArg(kernel, 2, Sizeof.cl_mem, Pointer.to(memObjects[2]));
// Set the work-item dimensions
long global_work_size[] = new long[]{N};
long local_work_size[] = new long[]{1};//This means each item is a separate workgroup
// Execute the kernel
clEnqueueNDRangeKernel(commandQueue, kernel, 1, null,global_work_size, local_work_size, 0, null, null); //execure each array in parallel
// Read the output data-->from c parameter /kalo dibutuhkan
//clEnqueueReadBuffer(commandQueue, memObjects[2], CL_TRUE, 0,N * Sizeof.cl_float, dst, 0, null, null);
/*BASIC END HERE*/
// Release kernel, program, and memory objects
clReleaseMemObject(memObjects[0]);
clReleaseMemObject(memObjects[1]);
clReleaseMemObject(memObjects[2]);
clReleaseKernel(kernel);
clReleaseProgram(program);
clReleaseCommandQueue(commandQueue);
clReleaseContext(context);
但对于calcDistanceCs（）和calcDistanceRs（），他们都需要读取txt文件。然后从那个文件我得到了这样的数组（stateArray []）：
FileReader fr;
LineNumberReader lnr;
String str;
int i;
System.out.println("Calculate distance Current State: ");
try{
// create new reader
fr = new FileReader("AttractorCs.txt");
lnr = new LineNumberReader(fr);
csLine=0;
// read lines till the end of the stream
while((str=lnr.readLine())!=null){
i=lnr.getLineNumber();
csBariske=i;
csBaris=str;
if(csBaris!=null){
List<ModEff> listState= new LinkedList<>();
String[] stateArray;
stateArray=csBaris.split("\t");
node1=BinaryStringtoBinaryByteArrAwal(stateArray[0]);
node2=BinaryStringtoBinaryByteArrAkhir(stateArray[2]);
}
if (csBariske % 2 == 1) {
it_attcGanj=String.valueOf(node1)+String.valueOf(node2);
}else{
it_attcGen=String.valueOf(node2)+String.valueOf(node1);
it_att=it_attcGanj+it_attcGen;
nodeCsArr = convertNodeArrToByteArr(it_att);
}
csLine++;
}
lnr.close();
}catch(Exception e){
// if any error occurs
e.printStackTrace();
}
System.gc();
return nodeCsArr;
这里是我需要阅读的示例文本文件： 00010000000000000000000000001000000000000000000000110000000001000000000010010111000000000000000000100000000000000001001000000000000000000000000000000001000000000000000000000000100000100000000000001000000000000001010000000000010000000000000000001000000000000001000000001000001100101000000000000010000000000010000000000000000000000000010000000000000110000000000001000000000000000000000100000000001001001110010000000000000000100000000000000000001000000000010000000010000000010000000000000000000010000000000100110000001000000000000000000000000001000000000000000100000000000100000000000000000000010000000000000000000000000100000000000000000000000000000000000000000000000000000000000000000000000000000000010000000000000010000000000000000100000110000000000000000000000000000000010000000000000000000010000000000000000000000100 1 0001000000000000000000000000100000000000000000000001000000000100000000000001001100000000000000000010000000000000000100100000000000000000000000000000000100000 0000000000000000000100000100000000000001000000000000001010000000000010000000000000000001000000000000001000000001000001100001000000000000010000000000010000000000000000000000000010000000000000110000000000001000000000000000000000100000000001001001110000000000000000000100000000000000000001000000000010000000010000000010000000000000000000000000000000100110000001000000000000000000000000001000000000000000100000000000100000000000000000000010000000000000000000000000100000000000000000000000000000000000000000000000000000000000000000000000000000000010000000000000010000000000000000100000110000000000000000000000000000000010000000000000000000010000000000000000000000100
从上面的例子中，我想拆分为： 第一阵列： 00010000000000000000000000001000000000000000000000110000000001000000000010010111000000000000000000100000000000000001001000000000000000000000000000000001000000000000000000000000100000100000000000001000000000000001010000000000010000000000000000001000000000000001000000001000001100101000000000000010000000000010000000000000000000000000010000000000000110000000000001000000000000000000000100000000001001001110010000000000000000100000000000000000001000000000010000000010000000010000000000000000000010000000000100110000001000000000000000000000000001000000000000000100000000000100000000000000000000010000000000000000000000000100000000000000000000000000000000000000000000000000000000000000000000000000000000010000000000000010000000000000000100000110000000000000000000000000000000010000000000000000000010000000000000000000000100 第二阵列： 00010000000000000000000000001000000000000000000000110000000001000000000010010111000000000000000000100000000000000001001000000000000000000000000000000001000000000000000000000000100000100000000000001000000000000001010000000000010000000000000000001000000000000001000000001000001100101000000000000010000000000010000000000000000000000000010000000000000110000000000001000000000000000000000100000000001001001110010000000000000000100000000000000000001000000000010000000010000000010000000000000000000010000000000100110000001000000000000000000000000001000000000000000100000000000100000000000000000000010000000000000000000000000100000000000000000000000000000000000000000000000000000000000000000000000000000000010000000000000010000000000000000100000110000000000000000000000000000000010000000000000000000010000000000000000000000100
每个数组由800个字节组成（来自数组0-799）。分隔符（分隔符），我将其粗体 1 。
答案 0 :(得分：1)
如果我正确理解您的问题，您似乎想要阅读fixed width flat file。
强烈建议：考虑使用像flatpack这样的库：http://flatpack.sourceforge.net/
以下是一些可能有用的其他链接：
1）显然你有一个“制表符分隔文件”。好的 - 您绝对可以将其拆分为String.split("\t")的字符串数组。
2）在你的示例中：
我有txt文件包含：1010101 1 1010111.我想要 将1010101作为数组a，将1010111作为数组b。
如果分隔符始终为“\ t1”，则可以使用。如果分隔符可能是"\t2"或"\t1000"，那么您可能希望：
使用String.split("\t")
在您的示例中，它将为您提供三个数组：“1010101”，“1010101”......和“1”。
相应地解析“array [1]”（值“1”）。
3）我不确定“阵列”是什么意思。
在您的示例中，值“1010101”和“1010101”将是 ONE，SINGLE 数组中的两个元素。
但这应该不是问题：您可以随时使用myArray[n].charAt(i)。
或者，您也可以随时将字符串转换为字符数组：
char[] charArray = myArray[n].toCharArray();
