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
     
      (10));    }    public void destory() {        if(pool != null) {            pool.shutdownNow();        }    }    private class Sum implements Callable
      
       {        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
       
        
         > taskList = new ArrayList<>();        int sumCounts = max - min;        int subCounts = sumCounts/threadNum;        int remainder = sumCounts%threadNum;        int mark = min;        for(int i = 0;i
         
          i){                subMax = subMin + subCounts;            }else{                subMax = mark + subCounts - 1;            }            mark = subMax + 1;            FutureTask
          
            task = new FutureTask
           
            (new Sum(subMin,subMax,arr)); taskList.add(task); pool.execute(new Thread(task)); } int sum = taskListSum(taskList); return sum; } private Integer taskListSum(List
            
             
              > taskList){ int sum = 0; for(FutureTask
              
                task : taskList){ try { sum += task.get(); } catch (InterruptedException e) { e.printStackTrace(); } catch (ExecutionException e) { e.printStackTrace(); } } return sum; } private class SumFloat implements Callable
               
                { 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
                
                 
                  > taskList = new ArrayList<>(); int sumCounts = max - min; int subCounts = sumCounts/threadNum; int remainder = sumCounts%threadNum; int mark = min; for(int i = 0;i
                  
                   i){ subMax = subMin + subCounts; }else{ subMax = mark + subCounts - 1; } mark = subMax + 1; FutureTask
                   
                     task = new FutureTask
                    
                     (new SumFloat(subMin,subMax,arr)); taskList.add(task); pool.execute(new Thread(task)); } Float sum = taskListSumFloat(taskList); return sum; } private Float taskListSumFloat(List
                     
                      
                       > taskList){ Float sum = 0f; for(FutureTask
                       
                         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）