Modern computing has many foundational building blocks, including central processing units (CPUs), graphics processing units (GPUs) and data processing units (DPUs).. However, what almost all modern ...

The best parallel processing libraries for Python. Ray: Parallelizes and distributes AI and machine learning workloads across CPUs, machines, and GPUs.; Dask: Parallelizes Python data science ...

In a separate effort to facilitate parallel computing, Nvidia recently launched its "2x in 4 Weeks. Guaranteed." program, encouraging programmers to use a directives-based model to double their ...

For example, a multiple shooting ... Space–time parallel computing: An approach that concurrently exploits parallelism in both spatial and temporal discretizations, ...

But there are examples of enterprises and institutions that have successfully made the leap to parallel computing. One is the country of Estonia. All of the nation’s computer systems now run on the ...

For example, it is often unclear if reported improvements are in the noise or observed by chance. In addition to distilling best practices from existing work, we propose statistically sound analysis ...

Quentin Stout and Christiane Jablonowski from the University of Michigan gave a nice introduction to parallel computing on Sunday. They covered everything from architecture to APIs to the politics ...

Each year, the Association for Computing Machinery honors a computer scientist for his or her contributions to the field. The prize, which comes with $250,000 thanks to Google and Intel, is named ...

The goal is "democratizing access to cheap, scalable parallel hardware." Each board has a dual-core ARM Cortex-A9 chip as its CPU, which can offload tasks to Adapteva's Epiphany co-processor.