CPU, GPU Potential for Visualization and Irregular Code
Conventional wisdom says that choosing between a GPU versus CPU architecture for running scientific visualization workloads or irregular code is easy. …
Conventional wisdom says that choosing between a GPU versus CPU architecture for running scientific visualization workloads or irregular code is easy. …
Many oil and gas exploration shops have invested many years and many more millions of dollars into homegrown codes, which is critical internally (competitiveness, specialization, etc.) …
Five years ago, many bleeding edge IT shops had either implemented a Hadoop cluster for production use or at least had a cluster set aside to explore the mysteries of MapReduce and the HDFS storage system. …
China’s massive Sunway TaihuLight supercomputer sent ripples through the computing world last year when it debuted in the number-one spot on the Top500 list of the world’s fastest supercomputers. …
There are individuals and companies that create whole new technologies for their own consumption and that sometimes open source them for others to help steer their development and fix their bugs. …
With the current data science boom, many companies and organizations are stepping outside of their traditional business models to scope work that applies rigorous quantitative methodology and machine learning – areas of analysis previously in the realm of HPC organizations. …
For a long time now, researchers have been working on automating the process of breaking up otherwise single-threaded code to run on multiple processors by way of multiple threads. …
In the prior two articles in this series (What Is SMP Without Shared Memory? …
This is the second in the series on the essentials of multiprocessor programming. …
Molecular dynamics codes have a wide range of uses across scientific research and represent a target base for a variety of accelerators and approaches, from GPUs to custom ASICs. …
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