The fact that your CPU is running at 100% does not tell much about how busy they are doing useful work. In your case, you are using more threads than cores so the 100% includes some context switching and uses memory unnecessarily (small impact for 100 threads), which is sub-optimal.
For CPU intensive task, I generally use this idiom:
private final int NUM_THREADS = Runtime.getRuntime().availableProcessors() + 1;
private final ExecutorService executor = Executors.newFixedThreadPool(NUM_THREADS);
Using more threads, as others have indicated, only introduces unnecessary context switching.
Obviously if the tasks do some I/O and other blocking operations, this is not applicable and a larger pool would make sense.
EDIT
To reply to @MartinJames comment, I have run a (simplistic) benchmark - result shows that going from a pool size = number of processors + 1 to 100 degrades the performance only slightly (let's call it 5%) - going to higher figures (1000 and 10000) does hit the performance significantly.
Results are the average of 10 runs:
Pool size: 9: 238 ms. //(NUM_CORES+1)
Pool size: 100: 245 ms.
Pool size: 1000: 319 ms.
Pool size: 10000: 2482 ms.
Code:
public class Test {
private final static int NUM_CORES = Runtime.getRuntime().availableProcessors();
private static long count;
private static Runnable r = new Runnable() {
@Override
public void run() {
int count = 0;
for (int i = 0; i < 100_000; i++) {
count += i;
}
Test.count += count;
}
};
public static void main(String[] args) throws Exception {
//warmup
runWith(10);
//test
runWith(NUM_CORES + 1);
runWith(100);
runWith(1000);
runWith(10000);
}
private static void runWith(int poolSize) throws InterruptedException {
long average = 0;
for (int run = 0; run < 10; run++) { //run 10 times and take the average
Test.count = 0;
ExecutorService executor = Executors.newFixedThreadPool(poolSize);
long start = System.nanoTime();
for (int i = 0; i < 50000; i++) {
executor.submit(r);
}
executor.shutdown();
executor.awaitTermination(10, TimeUnit.SECONDS);
long end = System.nanoTime();
average += ((end - start) / 1000000);
System.gc();
}
System.out.println("Pool size: " + poolSize + ": " + average / 10 + " ms. ");
}
}
