PeopleSoft NA Payroll 240K EE Benchmark with 16 Job Streams : Another Home Run for Sun
(
Originally posted on blogs.sun.com at:
http://blogs.sun.com/mandalika/entry/peoplesoft_na_payroll_240k_ee)
Poor
Steve A.[1] ... This entry is not about Steve A. though. It is about the new PeopleSoft NA Payroll benchmark result that Sun published today.
First things first. Here is the direct URL to our latest benchmark results:
PeopleSoft Enterprise Payroll 9.0 using Oracle for Solaris on a Sun SPARC Enterprise M4000 (16 job streams
[2] --
simply referred as 'stream' hereonwards)
The summary of the benchmark test results is shown below only for the 16 stream benchmarks. These numbers were extracted from the very first page of the benchmark results white papers where Oracle|PeopleSoft highlights the significance of the results and the actual numbers that are of interest to the customers. The results in the following table are sorted by the hourly throughput (payments/hour) in the descending order. The goal is to achieve as much hourly throughput as possible. Click on the link that is underneath the hourly throughput values to open corresponding benchmark result.
Oracle PeopleSoft North American Payroll 9.0 - Number of employees: 240,000 & Number of payments: 360,000Vendor | OS | Hardware Config | #Job Streams | Elapsed Time (min) | Hourly Throughput Payments per Hour |
---|
Sun | Solaris 10 5/09 |
1x Sun SPARC Enterprise M4000 with 4 x 2.53 GHz SPARC64-VII Quad-Core processors and 32 GB memory 1 x Sun Storage F5100 Flash Array with 40 Flash Modules for data, indexes 1 x Sun Storage J4200 Array for redo logs
| 16 | 43.78 | 493,376 |
HP | HP-UX | 1 x HP Integrity rx6600 with 4 x 1.6 GHz Intel Itanium2 9000 Dual-Core processors and 32 GB memory 1 x HP StorageWorks EVA 8100
| 16 | 68.07 | 317,320 |
This is all public information. Feel free to compare the hardware configurations and the data presented in both of the rows and draw your own conclusions. Since both Sun and HP used the same benchmark toolkit, workload and ran the benchmark with the same number of job streams, comparison should be pretty straight forward.
If you want to compare the 8 stream results, check the other blog entry:
PeopleSoft North American Payroll on Sun Solaris with F5100 Flash Array : A blog Reprise. Sun used the same hardware to run both benchmark tests with 8 and 16 streams respectively. We could have gotten away with 20+ Flash Modules (FMODs), but we want to keep the benchmark environment consistent with our prior benchmark effort around the same benchmark workload with 8 job streams. Due to the same hardware setup, now we can easily demonstrate the advantage of parallelism (
simply by comparing the test results from 8 and 16 stream benchmarks) and how resilient and scalable the F5100 Flash array is.
Our benchmarks showed an improvement of ~55% in overall throughput when the number of job streams were increased from 8 to 16. Also our 16 stream results showed ~55% improvement in overall throughput over HP's published results with the same number of streams at a maximum average CPU utilization of 45% compared to HP's maximum average CPU utilization of 89%. The half populated Sun Storage F5100 Flash Array played the key role in both of those benchmark efforts by demonstrating superior I/O performance over the traditional disk based arrays.
Before concluding, I would like to highlight a few known facts (just for the benefit of those people who may fall for the PR trickery):
- 8 job streams != 16 job streams. In other words, the results from an 8 stream effort is not comparable to that of a 16 stream result.
- The throughput should go up with increased number of job streams [ only up to some extent -- do not forget that there will be a saturation point for everything ]. For example, the throughput with 16 streams might be higher compared to the 8 stream throughput.
- The Law of Diminishing Returns applies to the software world too, not just for the economics. So, there is no guarantee that the throughput will be much better with 24 or 32 job streams.
Other blog posts and documents of interest:- Best Practices for Oracle PeopleSoft Enterprise Payroll for North America using the Sun Storage F5100 Flash Array or Sun Flash Accelerator F20 PCIe Card
- PeopleSoft Enterprise Payroll 9.0 using Oracle for Solaris on a Sun SPARC Enterprise M4000 (8 streams benchmark white paper)
- PeopleSoft North American Payroll on Sun Solaris with F5100 Flash Array : A blog Reprise
- App benchmarks, incorrect conclusions and the Sun Storage F5100
- Oracle PeopleSoft Payroll (NA) Sun SPARC Enterprise M4000 and Sun Storage F5100 World Record Performance
Notes:[1] Steve A. tried so hard and his best to make everyone else believe that HP's 16 job stream NA Payroll 240K EE benchmark results are on par with Sun's 8 stream benchmark results. Apparently Steve A. failed and gave up after we showed the world a few screenshots from a published and eventually withdrawn benchmark [
by HP ]. You can read all his arguments, comparisons etc., in the comments section of my other blog entry
PeopleSoft North American Payroll on Sun Solaris with F5100 Flash Array : A blog Reprise as well as in
Joerg Moellenkamp's blog entries around the same topic.
[2] In PeopleSoft terminology, a job stream is something that is equivalent to a thread.