使用线程池测试cpu的并发计算能力
接到一个需求是测试一下cpu并发计算能力,针对int和float求和单位时间能执行几次的问题。可能是服务器选型用到的参数。
开始使用的是fork-join,但是发现fork-join每次得到的结果值波动很明显不稳定(可能和fork-join的实现有关系,抽空研究一下),所以用了线程池的思路来实现
ps:
当然你可以把这篇文章作为线程池和Callable结合并发计算的一个demo来看
代码如下:
package com.company; import java.util.ArrayList; import java.util.List; import java.util.concurrent.ArrayBlockingQueue; import java.util.concurrent.Callable; import java.util.concurrent.ExecutionException; import java.util.concurrent.FutureTask; import java.util.concurrent.ThreadPoolExecutor; import java.util.concurrent.TimeUnit; /** * @author nf * 多线程累加求和 * */ public class CpuTestByThreadPool{ private ThreadPoolExecutor pool = null; public void init(int poolCount) { pool = new ThreadPoolExecutor( poolCount, poolCount*2, 30, TimeUnit.MINUTES, new ArrayBlockingQueue<Runnable>(10)); } public void destory() { if(pool != null) { pool.shutdownNow(); } } private class Sum implements Callable<Integer>{ private int subMin; private int subMax; private int[] arr; public Sum(int subMin,int subMax,int[] arr){ this.subMin = subMin; this.subMax = subMax; this.arr = arr; } @Override public Integer call() throws Exception { int sum = 0; for(int i = subMin;i <= subMax;i++){ sum += arr[i]; } return sum; } } /** * 求和范围是 min ~ max * @param min * @param max * @param threadNum * @return */ public Integer getSum(int min, int max,int[] arr, int threadNum){ int subMin; int subMax; List<FutureTask<Integer>> taskList = new ArrayList<>(); int sumCounts = max - min; int subCounts = sumCounts/threadNum; int remainder = sumCounts%threadNum; int mark = min; for(int i = 0;i<threadNum;i++){ subMin = mark; if(remainder!=0&&remainder>i){ subMax = subMin + subCounts; }else{ subMax = mark + subCounts - 1; } mark = subMax + 1; FutureTask<Integer> task = new FutureTask<Integer>(new Sum(subMin,subMax,arr)); taskList.add(task); pool.execute(new Thread(task)); } int sum = taskListSum(taskList); return sum; } private Integer taskListSum(List<FutureTask<Integer>> taskList){ int sum = 0; for(FutureTask<Integer> task : taskList){ try { sum += task.get(); } catch (InterruptedException e) { e.printStackTrace(); } catch (ExecutionException e) { e.printStackTrace(); } } return sum; } private class SumFloat implements Callable<Float>{ private int subMin; private int subMax; private Float[] arr; public SumFloat(int subMin,int subMax,Float[] arr){ this.subMin = subMin; this.subMax = subMax; this.arr = arr; } @Override public Float call() throws Exception { Float sum = 0f; for(int i = subMin;i <= subMax;i++){ sum += arr[i]; } return sum; } } /** * 求和范围是 min ~ max * @param min * @param max * @param threadNum * @return */ public Float getSumFloat(int min, int max,Float[] arr, int threadNum){ int subMin; int subMax; List<FutureTask<Float>> taskList = new ArrayList<>(); int sumCounts = max - min; int subCounts = sumCounts/threadNum; int remainder = sumCounts%threadNum; int mark = min; for(int i = 0;i<threadNum;i++){ subMin = mark; if(remainder!=0&&remainder>i){ subMax = subMin + subCounts; }else{ subMax = mark + subCounts - 1; } mark = subMax + 1; FutureTask<Float> task = new FutureTask<Float>(new SumFloat(subMin,subMax,arr)); taskList.add(task); pool.execute(new Thread(task)); } Float sum = taskListSumFloat(taskList); return sum; } private Float taskListSumFloat(List<FutureTask<Float>> taskList){ Float sum = 0f; for(FutureTask<Float> task : taskList){ try { sum += task.get(); } catch (InterruptedException e) { e.printStackTrace(); } catch (ExecutionException e) { e.printStackTrace(); } } return sum; } /** * @param args * 测试 * @throws InterruptedException */ public static void main(String[] args) throws InterruptedException{ //修改这三个参数 final int arrSize = 2800000,sleeptime=10000; final int poolCount = 10; int[] arr = new int[arrSize]; for (int i = 0; i < arrSize; i++) { arr[i] = i + 1; } Float[] arrFloat = new Float[arrSize]; for (int i = 0; i < arrSize; i++) { arrFloat[i] = i + (((float)i) / 3f); } CpuTestByThreadPool sumCalculator = new CpuTestByThreadPool(); sumCalculator.init(poolCount); long startTime = 0L; long endTime = 0L; long countL=0L,countF=0L; startTime = System.nanoTime(); while ((endTime-startTime)<10000000000L) {//10秒 sumCalculator.getSum(0, arrSize,arr, poolCount); endTime = System.nanoTime(); countL++; } System.out.println(countL); Thread.sleep(sleeptime); endTime = 0L; startTime = System.nanoTime(); while ((endTime-startTime)<10000000000L) { sumCalculator.getSumFloat(0, arrSize, arrFloat, poolCount); endTime = System.nanoTime(); countF++; } System.out.println(countF); sumCalculator.destory(); System.out.println("TPCC= " + (countL+countF)/2 + "tpmC"); } }
可以通过修改arrSize = 2800000;poolCount = 10;这两个参数匹配自己的机器(让运行时cpu内核占满就行了)