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If you take a look at the chart, it shows clearly this disparity in theoretical peak performance versus the actual application-like benchmark approach of HPCG. “We don’t have a lot of information about that system still, so it is hard to pinpoint why this is, but you can see other examples of this where there is a high Linpack ranking that is quite a bit different from what we see in HPCG.” What is most interesting is that if you take the Linpack results versus HPCG, some systems, like the Sunway machine, are far slower,” Heroux says. Not only will there be more submissions, but with the arrival of new processors on an increasing number of systems, most notably Knights Landing (which will be on the Trinity machine at Los Alamos National Lab in time for SC16-not to mention on several other top 50 supercomputers), it will also offer a richer set of results to understand potential application performance potential-blended with Linpack results, of course. Of the 500 supercomputers that make the Linpack-based Top 500 list, the newer HPCG benchmark had over 80 participants, a number that Heroux tells The Next Platform will continue to grow. The top ten listing for HPCG seen above makes handy reference to the peak Linpack performance for balance. And in high performance computing, an award like this takes serious scrutiny for both the scientific value, the application’s scalability and complexity, and of course, the validation that the science being done at scale is doing so on a machine that was designed for real HPC versus toppling the Top 500 charts. That award goes to teams who can use as much of a supercomputer’s cores as possible for actual scientific applications. While the metrics from HPCG are not great, the system’s value has been demonstrated in other real-world application contexts, most notably because the system is used for three Gordon Bell prize finalists. To preface the HPCG results as they relate to the new Chinese top supercomputer, however, we should note that even though TaihuLight shows rather abysmal performance on HPCG, this does not necessarily mean it is a stunt system (as some thought the former top Chinese supercomputer, Tianhe-2 was, to some extent). That does not sound good, but remember that even the other systems on the list are getting between 2-3% percent at the top, with Japan’s K Computer showing the highest percent of that theoretical peak potential’s actual utilization at 4.9%. 3% system utilization based on the theoretical peak. While the TaihuLight supercomputer rocked the Top 500 supercomputer list, its performance on HPCG showed that it is getting just. As it turns out, HPCG and its focus on real application patterns, tells another story. Performance and architectural details on that machine can be found here, but most of that discussion is based on its performance on the Linpack benchmark. This system made world headlines this week with its dramatically superior performance that shatters the performance record for supercomputing by a long shot. If there was ever a time when the value of such a benchmark could be clearly seen it was with today’s announcement of the latest Linpack Top 500 results that put the apparently spectacular performance of the new Sunway TaihuLight supercomputer into clearer focus. Jack Dongarra (one of the original founders of the Linpack benchmark and Top 500 list of supercomputers) and Sandia National Lab’s Michael Heroux developed the High Performance Conjugate Gradient ( HPCG) benchmark, a companion metric to balance perspectives on performance that is a growing companion to the more widely-known Linpack results. To answer demands from supercomputing sites that a metric be developed that emphasizes data movement over sheer number crunching peak potential, Dr. While raw floating point peak performance is a competitive fuel, for those engaged in scientific computing at scale, determining what makes a machine valuable is far more nuanced. This shift in value stands to reason, since larger machines mean more data coursing through the system, thus an increased reliance on memory and the I/O subsystem, among other factors. However, many have argued the benchmark is getting long in tooth with its myopic focus on sheer floating point performance over other important factors that determine a supercomputer’s value for real-world applications. When we cover the bi-annual listing of the world’s most powerful supercomputers, the metric at the heart of those results, the high performance Linpack benchmark, the gold standard for over two decades, is the basis.