With data volumes now outpacing Moore’s Law, there is a move to look beyond conventional hardware and software tools. Accelerators like GPUs and the Intel MIC architecture have extended performance goals for many HPC-class workloads. Although field-programmable gate arrays (FPGAs) have not seen the same level of adoption for traditional HPC workloads, a subset of big data Read more…
While discussions of HPC architectures have long centered on performance gains, that is not the only measure of success, according to Petteri Laakso of Vector Fabrics. Spurred by ever-proliferating core counts, programmability is taking on new prominence. Vector Fabrics is a Netherlands-based company that specializes in multicore software parallelization tools, so programmability is high on Read more…
When it comes to mainstream adoption of the use of GPUs and other accelerators, one of the primary barriers lies in programmability. While the vendor communities around accelerators have pushed to flatten the learning curve, the fact remains that it takes special effort on the part of ordinary developers to undertake the educational process. In this in-depth audio feature, we talk to Rice University researcher, Max Grossman about how Java…
<img src=”http://media2.hpcwire.com/hpcwire/future_insight_200x.jpg” alt=”” width=”100″ height=”58″ />The top research stories of the week include novel methods of data race detection; a comparison of predictive laws; a review of FPGA’s promise; GPU virtualization using PCI Direct pass-through; and an analysis of the Amazon Web Services High-IO platform.
<img style=”float: left;” src=”http://media2.hpcwire.com/hpcwire/V72000T_chip.jpg” alt=”” width=”105″ height=”77″ />Thanks to shrinking semiconductor process geometries, the newest FPGAs have more usable transistors than ever before and are now capable of considerable floating point (FP) performance. That makes them candidates for more generalized use in high performance computing. This article describes the FP capabilities of Xilinx’s new Virtex-7 FPGA and how it stacks up against a generic 16-core CPU.
Additional performance increases for supercomputers are being confounded by three walls: the power wall, the memory wall and the datacenter wall (the “wall wall”). To overcome these hurdles, the market is currently looking to a combination of four strategies: parallel applications development, adding accelerators to standard commodity compute nodes, developing new purpose-built systems, and waiting for a technology breakthrough.
It’s been a little over a year since Nimbix announced the initial beta launch of its Nimbix Accelerated Compute Cloud (NACC). During the SC11 show in Seattle last week, HPC in the Cloud sat down with Nimbix Co-Founder and CEO Steve Hebert to find out where the company fits in with the small-but-growing stable of cloud providers who specialize in supporting HPC workloads.
Indiana-based MNB Technologies is a small company with big aspirations. The soon-to-be-public corporation is developing an expert-system based development suite designed to greatly simplify the programming of HPC accelerators, in particular FPGAs and GPU. To that end, the company recently announced the beta availability of its flagship product, hprcARCHITECT.
Acceleration technology is all the rage these days in high performance computing. With the emergence of GPGPUs into the mainstream, a whole new sub-industry has coalesced around acceleration solutions based on the latest GPUs. Maxeler Technologies, however, has made a nice living delivering FPGA acceleration to a rather elite customer base.
For the past several years, Field Programmable Gate Arrays (FPGAs) have been getting large enough to compete with microprocessors in floating-point performance. Using the theoretical peak performance numbers, the FPGA’s floating-point performance is growing faster than microprocessors. This article calculates the peak performance for several FPGA devices from Xilinx and compares them to a reference microprocessor for equivalent time periods and shows that this gap in performance is growing.