Today STAC released audited STAC-A2 Benchmark results for a server using the just-announced Nvidia Tesla K80 dual-GPU Accelerator board.
Search Results for: gpu
“Over at the Parallel for All Blog, Everett Phillips and Massimiliano Fatica write that GPUs offer good acceleration on the new HPCG benchmark that has been designed to augment Linpack as a measure of performance for the TOP500. Their GPU porting strategy focused on parallelizing the Symmetric Gauss-Seidel smoother (SYMGS), which accounts for approximately two thirds of the benchmark flops.”
GPUdb is a scalable, distributed database with SQL-style query capability, capable of storing Big Data. Developers using the GPUdb API add data, and query the data with operations like select, group by, and join. GPUdb includes many operations not available in other “cloud database” offerings. GPUdb applies a new (patented) concept in database design that puts emphasis on leveraging the growing trend of many-core devices. By building GPUdb from the ground up around this new concept we are able to provide a system that merges the query needs of the traditional relational database developer with the scalability demands of the modern cloud-centric enterprise.
Today IBM introduced a new series of GPU-accelerated systems capable of handling massive amounts of computational data faster and at a nearly 20% better price performance than comparable Intel-based systems – providing clients a superior alternative to closed, commodity-based data center servers. The vastness of Big Data—of the 2.5 quintillion bytes of data generated on […]
“Although the use of GPUs has generalized nowadays, including GPUs in current HPC clusters presents several drawbacks mainly related with increased costs. In this talk we present how the use of remote GPU virtualization may overcome these drawbacks while noticeably increasing the overall cluster throughput. The talk presents real throughput measurements by making use of the rCUDA remote GPU virtualization middleware.”