Throughput computing series: Parallel commands (pbzip2)

Monday Jan 14, 2008

In this installment of the throughput computing series, I will explore how to get parallelism from the system point of view. The system administrator who first begins to configure the system will start forming impressions from the moment the shrink wrap comes off the server. First impressions and potential parallel options will be explored in this entry.

Off with the shrink-wrap... on with the install

Unfortunately, most installation processes involve a fair number of single-threaded procedures. As mentioned before, the CMT processor is designed to be a processor that optimizes the overall throughput of a server - often to the detriment of single threaded processes. There are several schools of thought on this one. First is, why bother - the install process happens but once and it really doesn't matter. That is true for most typical environments. But the current trend toward grid computing and virtualization makes "time to provision" often a critical factor. To help speed provisioning, there are some things that can be done by using parallelized commands and concurrency.

pbzip2 to the rescue

A very common time-consuming part of provisioning is the packing/unpacking of SW packages. Commonly, gzip or bzip is used to unpack data and packages, but this is not a parallel program. Fortunately, there is a parallel version of bzip that has been made available. "pbzip2" allows you to specify the level of parallelism in order to speed the compression/decompression process.

I spent a little time experimenting with the pbzip program after repeated interactions that always seemed to come back to "gzip" performance. I decided to do some quick benchmarks with pbzip2 using both the T2000(8core@1.4GHz) and v20z(AMD 2cores@2.2GHz).

pbzip2 benchmark

The setup used a 135M text file. This file was the trade_history.txt created using the egen program distributed by the tpc council for the TPC-E benchmark. This file was compressed using the following simple test script:

#!/bin/ksh for i in 1 2 4 8 16 32 do print "pbzip2 compress: ${i} threads\n" timex pbzip2 -p${i} small.txt print "pbzip2 decompress: ${i} threads\n" timex pbzip2 -d -p${i} small.txt.bz2 done

At lower thread counts, the v20z with two AMD cores does better. This is expected since the AMD x64 processor is optimized single-threaded performance. But you can see as you crank up the thread count, the T2000 starts to really shine. This demonstrates my main point that to push massive throughput within a single application, you need lots of threads and parallelism.

...The next entry will explore how concurrency and parallelism can help improve build times.