ByteEasy

I'm using their PI example. The Performance gains are great and when you see the code below you will realize that PICloud is really easy and intuitive to use. I'll be moving some of my python jobs to them. 0.0 0.0160000324249 0.047000169754 0.483999967575 4.64100003242 46.5150001049 Process Location Number of Tests Number in Parallel Wall Clock Time (sec) Pi calcPiLocal local 1 10 2 0.00 3.16000000 calcPiCloud cloud 8 10 2 30.37 3.04000000 calcPiLocal local 1 10 3 0.00 3.13200000 calcPiCloud cloud 8 10 3 5.31 3.08000000 calcPiLocal local 1 10 4 0.02 3.13640000 calcPiCloud cloud 8 10 4 4.31 3.13200000 calcPiLocal local 1 10 5 0.05 3.13664000 calcPiCloud cloud 8 10 5 1.22 3.13840000 calcPiLocal local 1 10 6 0.48 3.14185200 calcPiCloud cloud 8 10 6 2.30 3.14116000 calcPiLocal local 1 10 7 4.64 3.14092240 calcPiCloud cloud 8 10 7 2.31 3.14099920 calcPiLocal local 1 10 8 46.52 3.14138168 calcPiCloud cloud 8 10 8 8.50 3.14139276 calcPiLocal local 1 10...

Couchdb 0.11.0 2x3 QUAD-Core Intel Xeon 16 GB 667Mhz DDR2 OS X 10.6.4 Inserting NUM BLOCK time Bytes Mb/s records/s 1 1 0.0030 1 0.000 330 10 1 0.0251 100 0.004 398 1000 1 3.2415 1000000 0.308 308 10000 1 34.6263 100000000 2.888 289 1000 10 3.4122 10610000 3.109 2931 100 100 1.5112 10601000 7.015 6617 10 1000 1.9464 10600100 5.446 5138 2 5000 2.3308 10600020 4.548 4290 1 10000 2.0068 10600010 5.282 4983 10 10000 15.7176 106000100 6.744 6362 Average Top: 33423 beam.smp 48.9 05:42.89 13 0 62 151- 39M- 264K 33421 CouchDBX 12.9 00:52.85 6/1 3 124- 322 77M- 29M