From the Editor | Main Blog Index
June 30, 2009
The engineering team at Advanced Clustering Technologies is at it again. A couple of weeks ago, they published the results of the High Performance Linpack (HPL) benchmark for comparable Intel Nehalem- and AMD Istanbul-based systems, which I discussed in a previous article. Those results had Istanbul edging out Nehalem for Linpack bragging rights.
Now the engineers at Advanced Clustering Technologies have pitted those same microprocessors against each other using the STREAM benchmark and have posted the results on their Web site. STREAM is part of the HPC Challenge suite and measures sustainable memory bandwidth -- one of the most important attributes of high performance computing systems today.
Memory bandwidth, or lack thereof, has become increasingly significant for many applications, since as core counts increase, computational power is racing ahead of memory performance. Like HPL, STREAM is a synthetic benchmark, but, in general, if an application is memory constrained, the STREAM benchmark is a good indicator of relative performance.
The STREAM results for the Nehalem and Istanbul offered no surprises. If you've been following the x86 rivalry, you've probably guessed that Intel's Nehalem (Xeon 5500) processor, with its more advanced memory subsystem, bests AMD's Istanbul Opteron, which relies on the older DDR2 technology. According to Advanced Clustering Technologies engineer Shane Corder:
Even the slowest memory speed on a Xeon 5500 processor bests the fastest produced by the Opteron by as much as 20%; comparing the Opteron to the fastest Xeon, the Xeon outperforms by over 75%. The Xeon 5500 gets these much higher memory bandwidth results because of tri-channel instead of dual-channel memory, the increased clock speed of DDR3 (up to 1333MHz), and the fast point-to-point CPU interconnect provided by its Quick Path Interconnect.
One other noteworthy data point is that STREAM performance on the six-core Istanbul turned out to be slightly worse than on the quad-core Shanghai. The Advanced Clustering Technologies folks attribute this to the two extra Istanbul cores having to contend for bandwidth on the same number of memory controllers (two) that are present in the Shanghai chip. As the company did with the Linpack results, the results were also described in terms of price-performance:
When you add cost per machine into the mix, the results still show the Xeon 5500 series with a clear lead. The Xeon machine as configured has a price of approximately $3,800 while the Opteron is priced at $3,500. This gives the Xeon a rate of 9.8 megabytes per second per dollar vs. 5.9 megabytes per second per dollar for the Opteron: a 66% advantage for the Intel Xeon 5500 series.
As before, the caveat is that the synthetic benchmark results may not correspond to real-world apps. The recommendation from Advanced Clustering Technologies is that you use your own codes to figure out which processor and system configuration is going to give you the most bang for the buck.
Posted by Michael Feldman - June 30, 2009 @ 10:55 AM, Pacific Daylight Time
![]()
Michael Feldman is the editor of HPCwire.
No Recent Blog Comments
In quieter times, sounding the bell of funding big science with big systems tends to resonate further than when ears are already burning with sour economic and national security news. For exascale's future, however, the time could be ripe to instill some sense of urgency....
Read more...
In a recent solicitation, the NSF laid out needs for furthering its scientific and engineering infrastructure with new tools to go beyond top performance, Having already delivered systems like Stampede and Blue Waters, they're turning an eye to solving data-intensive challenges. We spoke with the agency's Irene Qualters and Barry Schneider about..
Read more...
Large-scale, worldwide scientific initiatives rely on some cloud-based system to both coordinate efforts and manage computational efforts at peak times that cannot be contained within the combined in-house HPC resources. Last week at Google I/O, Brookhaven National Lab’s Sergey Panitkin discussed the role of the Google Compute Engine in providing computational support to ATLAS, a detector of high-energy particles at the Large Hadron Collider (LHC).
Read more...
May 23, 2013 |
The study of climate change is one of those scientific problems where it is almost essential to model the entire Earth to attain accurate results and make worthwhile predictions. In an attempt to make climate science more accessible to smaller research facilities, NASA introduced what they call ‘Climate in a Box,’ a system they note acts as a desktop supercomputer.
Read more...
May 22, 2013 |
At some point in the not-too-distant future, building powerful, miniature computing systems will be considered a hobby for high schoolers, just as robotics or even Lego-building are today. That could be made possible through recent advancements made with the Raspberry Pi computers.
Read more...
May 16, 2013 |
When it comes to cloud, long distances mean unacceptably high latencies. Researchers from the University of Bonn in Germany examined those latency issues of doing CFD modeling in the cloud by utilizing a common CFD and its utilization in HPC instance types including both CPU and GPU cores of Amazon EC2.
Read more...
May 15, 2013 |
Supercomputers at the Department of Energy’s National Energy Research Scientific Computing Center (NERSC) have worked on important computational problems such as collapse of the atomic state, the optimization of chemical catalysts, and now modeling popping bubbles.
Read more...
05/10/2013 | Cleversafe, Cray, DDN, NetApp, & Panasas | From Wall Street to Hollywood, drug discovery to homeland security, companies and organizations of all sizes and stripes are coming face to face with the challenges – and opportunities – afforded by Big Data. Before anyone can utilize these extraordinary data repositories, however, they must first harness and manage their data stores, and do so utilizing technologies that underscore affordability, security, and scalability.
04/15/2013 | Bull | “50% of HPC users say their largest jobs scale to 120 cores or less.” How about yours? Are your codes ready to take advantage of today’s and tomorrow’s ultra-parallel HPC systems? Download this White Paper by Analysts Intersect360 Research to see what Bull and Intel’s Center for Excellence in Parallel Programming can do for your codes.
In this demonstration of SGI DMF ZeroWatt disk solution, Dr. Eng Lim Goh, SGI CTO, discusses a function of SGI DMF software to reduce costs and power consumption in an exascale (Big Data) storage datacenter.
The Cray CS300-AC cluster supercomputer offers energy efficient, air-cooled design based on modular, industry-standard platforms featuring the latest processor and network technologies and a wide range of datacenter cooling requirements.