Core Costs

Lately, we’ve been experimenting with multi-core programming. This is a technique whereby tasks are split up among multiple processors in order to decrease processing time.

To appreciate the advantages of multi-core programs, and the number of cores available, consider this example:

  • We recently calculated that a big, ugly, multivariate probability block model would require 167 days to run using a moderately high-end laptop (ASUS G75VW – quad-core i7-3820QM). This machine processes data at a rate of about 70 gigaFLOPS (FLOP = Floating Operations Per Second). That’s 70,000,000,000 operations per second.

167 Days

 

  • For the sake of comparison, the new Cray XC40 is capable of running at 100 petaFLOPS. That’s 100,000,000,000,000,000 operations per second or 14,286x faster than the ASUS laptop. The same modeling process would therefore require about 17 minutes on the Cray.

17 Minutes

The ASUS G75VW costs about $1,599 and weighs 8.7 pounds.

The Cray XC40 costs about $156,000,000 and weighs 140 tons. [Note: Price is for 16petaFLOP/480,000-core version. Unable to obtain price for 100petaFLOP/1,000,000-core configuration.]

The following table provides some cost-per-processor examples:

Computer

Price ($)

Processors

$ Per Processor

Lenovo Thinkpad X140e

279

4

70

Lenovo ThinkServer TD340

906

6

151

Adamant AMD FX 8350

953

8

119

Apple Mac Pro

9,499

12

791

HP Z820

6,599

12

549

Mediaworkstations i-X2

14,424

24

60

Cray XC40

156,000,000

480,000

325

Note: This comparison does not take clock speed into account.

 

Conclusion: The current generation of quad-core i7 and AMD processors represent the best bang-per-buck with the very notable exception of the Mediaworkstations i-X2.

Mediaworkstations i-X2: $14,414 w/2 12-Core Intel Xeon E5-2697 (24 Cores)

Postscript: This blog entry was written while waiting for a model to be interpolated on a quad-core machine and fantasizing about more cores to multi-thread.

 

 

 

2 thoughts on “Core Costs

    • Hi Scot; For now, I’m pursuing the multicore approach while Mitch is investigating the GPU approach. I’m a bit leery about card dependencies/incompatibilities but this is probably because I’m a curmudgeon. Best regards, Jim Reed.