Java 7 measurements

This table shows 4 measurements - CPU Time, Elapsed Time, Memory and Code.

Each row shows those measurements for a particular Java 7 program with a particular command-line input value N.

This table shows the current Java 7 programs.

Program Source Code	N	CPU secs	Elapsed secs	Memory KB	Code B
binary-trees #2	12	0.15	0.12	?	603
binary-trees #2	16	0.94	0.82	148,920	603
binary-trees #2	20	16.90	12.75	485,056	603
binary-trees	12	0.20	0.47	3,664	1007
binary-trees	16	0.95	0.55	78,180	1007
binary-trees	20	21.35	9.21	525,420	1007
binary-trees-redux #2	12	0.16	0.13	?	607
binary-trees-redux #2	16	0.87	0.71	53,560	607
binary-trees-redux #2	20	234.19	69.69	134,176	607
chameneos-redux #2	60,000	0.45	0.20	?	1429
chameneos-redux #2	600,000	4.18	1.40	29,324	1429
chameneos-redux #2	6,000,000	37.64	12.59	30,756	1429
chameneos-redux #3	60,000	0.72	0.28	212	1267
chameneos-redux #3	600,000	3.42	1.05	33,084	1267
chameneos-redux #3	6,000,000	29.11	8.55	48,252	1267
chameneos-redux	60,000	0.31	0.16	?	1770
chameneos-redux	600,000	1.38	0.89	17,528	1770
chameneos-redux	6,000,000	6.57	5.19	29,584	1770
fannkuch-redux	10	0.72	0.24	212	1282
fannkuch-redux	11	5.22	1.38	13,924	1282
fannkuch-redux	12	67.91	17.17	14,460	1282
fannkuch-redux #2	10	0.81	0.76	14,700	514
fannkuch-redux #2	11	5.73	5.69	14,672	514
fannkuch-redux #2	12	87.01	86.98	14,712	514
fasta #2	250,000	0.23	0.18	?	1240
fasta #2	2,500,000	1.05	0.97	15,300	1240
fasta #2	25,000,000	7.81	7.72	15,240	1240
fasta #4	250,000	0.19	0.15	?	1507
fasta #4	2,500,000	0.69	0.62	14,428	1507
fasta #4	25,000,000	5.07	4.99	14,976	1507
fasta-redux #3	250,000	0.13	0.11	?	1443
fasta-redux #3	2,500,000	0.36	0.31	212	1443
fasta-redux #3	25,000,000	1.90	1.85	14,500	1443
k-nucleotide #2	250,000	1.48	0.48	28,148	1602
k-nucleotide #2	2,500,000	5.64	1.68	80,800	1602
k-nucleotide #2	25,000,000	44.83	12.93	494,264	1602
k-nucleotide #3	250,000	1.31	0.48	28,144	1630
k-nucleotide #3	2,500,000	6.31	2.08	132,884	1630
k-nucleotide #3	25,000,000	46.77	13.37	494,772	1630
mandelbrot	1,000	0.34	0.30	212	665
mandelbrot	4,000	2.87	2.83	14,252	665
mandelbrot	16,000	42.94	42.90	14,240	665
mandelbrot #2	1,000	0.26	0.12	?	796
mandelbrot #2	4,000	1.88	0.54	15,804	796
mandelbrot #2	16,000	27.14	6.90	67,612	796
mandelbrot #6	1,000	0.30	0.13	?	802
mandelbrot #6	4,000	2.04	0.58	15,804	802
mandelbrot #6	16,000	29.56	7.55	67,600	802
mandelbrot #3	1,000	0.44	0.20	?	903
mandelbrot #3	4,000	3.31	0.96	16,304	903
mandelbrot #3	16,000	42.29	10.72	68,128	903
meteor-contest	2,098	0.90	0.81	16,232	4368
meteor-contest #2	2,098	0.42	0.22	240	5177
n-body #2	500,000	0.36	0.33	212	1424
n-body #2	5,000,000	2.54	2.52	13,916	1424
n-body #2	50,000,000	24.41	24.39	13,976	1424
pidigits	2,000	1.79	1.16	153,492	800
pidigits	6,000	10.33	9.41	233,988	800
pidigits	10,000	28.56	27.50	358,248	800
pidigits #2	2,000	Failed			938
pidigits #3	2,000	1.82	0.66	32,684	1826
pidigits #3	6,000	5.72	2.36	34,072	1826
pidigits #3	10,000	11.75	5.12	46,488	1826
pidigits #4	2,000	1.77	1.00	26,356	1808
pidigits #4	6,000	4.55	2.33	32,284	1808
pidigits #4	10,000	11.76	5.15	44,092	1808
regex-dna #5	50,000	0.91	0.36	212	929
regex-dna #5	500,000	3.48	1.21	84,608	929
regex-dna #5	5,000,000	27.09	9.43	708,060	929
regex-dna #7	50,000	0.63	0.41	240	1284
regex-dna #7	500,000	2.73	2.44	25,672	1284
regex-dna #7	5,000,000	22.16	21.90	556,704	1284
regex-dna #6	50,000	Failed			1410
regex-dna #2	50,000	0.92	0.38	216	1534
regex-dna #2	500,000	4.84	1.67	97,928	1534
regex-dna #2	5,000,000	41.89	13.60	730,784	1534
regex-dna #4	50,000	0.78	0.49	28,540	921
regex-dna #4	500,000	3.26	2.67	60,992	921
regex-dna #4	5,000,000	26.33	24.67	720,412	921
reverse-complement #4	250,000	0.23	0.15	?	592
reverse-complement #4	2,500,000	0.53	0.44	36,472	592
reverse-complement #4	25,000,000	3.07	2.99	476,240	592
reverse-complement #3	250,000	0.30	0.20	?	1661
reverse-complement #3	2,500,000	0.56	0.33	216	1661
reverse-complement #3	25,000,000	2.93	1.52	294,784	1661
reverse-complement #7	250,000	0.42	0.30	212	1640
reverse-complement #7	2,500,000	0.71	0.85	40,048	1640
reverse-complement #7	25,000,000	2.39	8.78	263,532	1640
reverse-complement #6	250,000	0.16	0.12	?	745
reverse-complement #6	2,500,000	0.37	0.31	212	745
reverse-complement #6	25,000,000	1.92	1.68	511,484	745
spectral-norm #2	500	0.48	0.20	?	950
spectral-norm #2	3,000	5.23	1.41	14,188	950
spectral-norm #2	5,500	16.39	4.21	14,740	950
spectral-norm	500	0.30	0.25	240	514
spectral-norm	3,000	5.16	5.10	14,704	514
spectral-norm	5,500	16.90	16.85	15,236	514
thread-ring #3	500,000	4.82	4.33	26,420	530
thread-ring #3	5,000,000	41.82	38.25	26,640	530
thread-ring #3	50,000,000	405.33	373.96	288,644	530

Java 7 : ubiquitous jit server virtual machine

java version "1.7.0_11"
Java(TM) SE Runtime Environment (build 1.7.0_11-b21)
Java HotSpot(TM) Server VM (build 23.6-b04, mixed mode)

Home Page: Java SE at a Glance

Download: Java SE Downloads

Let's see how much, or how little, the time taken to invoke the JVM might contribute to the usual Java program times shown in the benchmarks game. Here are some additional (Intel® Q6600® quad-core) elapsed time measurements, taken after the Java programs started and before they exited.

In the first case (Cold), we simply started and measured the program 66 times; and then discarded the first measurement leaving 65 data points.

   public static void main(String[] args){
      for (int i=0; i<1; ++i){ 
         System.gc(); 
         long t1 = System.nanoTime();
         nbody.program_main(args);
         long t2 = System.nanoTime();
         System.err.println( String.format( "%.6f", (t2 - t1) * 1e-9 ) );         
      }
   }

In the second case (Warmed), we started the program once and repeated measurements again and again and again 66 times without restarting the JVM; and then discarded the first measurement leaving 65 data points.

   public static void main(String[] args){
      for (int i=0; i<66; ++i){ 
         System.gc(); 
         long t1 = System.nanoTime();
         nbody.program_main(args);
         long t2 = System.nanoTime();
         System.err.println( String.format( "%.6f", (t2 - t1) * 1e-9 ) );         
      }
   }

Compare these additional measurements against the usual Java program measurements shown in the benchmarks game --

"1.7.0_06" Java HotSpot(TM) 64-Bit Server VM
System.nanoTime()	1) Cold		2) Warmed
	mean	σ	mean	σ	usual
meteor contest	0.0118s	0.0007	0.0016s	0.0002	0.22s
fasta-redux	2.45s	0.00	2.32s	0.00	2.51s
spectral-norm	4.44s	0.02	4.20s	0.16	4.51s
pidigits	4.69s	0.09	4.44s	0.05	4.61s
fasta	5.07s	0.46	4.84s	0.02	5.13s
chameneos-redux	5.84s	0.46	5.70s	0.48	5.65s
mandelbrot	7.93s	0.23	7.99s	0.01	7.02s
k-nucleotide	8.09s	0.28	--	--	8.05s
regex-dna	8.65s	0.27	--	--	8.61s
binary-trees	10.54s	0.28	7.66s	0.16	9.08s
fannkuch-redux	16.89s	1.32	17.26s	0.10	17.38s
nbody	22.43s	0.00	22.41s	0.00	22.50s
binary-trees-redux	34.15s	0.39	33.93s	0.31	33.38s

The largest and most obvious effects of bytecode loading and dynamic optimization can be seen with the meteor-contest program which only runs for a fraction of a second.

Home Conclusions License Play

Ubuntu : Intel® Q6600® quad-coreComputer Language Benchmarks Game [[ Play ]]

Java 7 measurements

Java 7 : ubiquitous jit server virtual machine

Ubuntu : Intel® Q6600® quad-core
Computer Language Benchmarks Game [[ Play ]]