Today STAC, the financial industry benchmarking organization, announced record performance results on the new Tesla K80 Dual-GPU Accelerator.
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GPU-accelerated computing is the use of a graphics processing unit (GPU) together with a CPU to accelerate scientific, analytics, engineering, consumer, and enterprise applications. Pioneered in 2007 by NVIDIA, GPU accelerators now power energy-efficient datacenters in government labs, universities, enterprises, and small-and-medium businesses around the world. GPUs are accelerating applications in platforms ranging from cars, to mobile phones and tablets, to drones and robots.
“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.