Cloudian’s AI data storage solutions are future-proofed for next-generation AI applications. As GPUs continue to break ...

Since then we have seen parallel processing techniques executed in many forms. In stacks of Macs. At Google. In "distributed computing" systems like the famous SETI@Home project. And now in chips.

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 ...

Concurrent and parallel systems form the bedrock of modern computational infrastructures, enabling vast improvements in processing speed, efficiency and scalability. By orchestrating multiple ...

Discover how Sarvesh Kumar Gupta's innovative distributed database pipeline transformed financial data processing, maximising ...

AWS recently announced a distributed map for Step Functions, a solution for large-scale parallel data processing. Optimized for S3, the new feature of the AWS orchestration service targets interactive ...

As a result, parallel computation starts almost immediately with the first chunk of data. Using the parallel in-memory grid can result in much faster execution of the post-processing operations than ...

It’s ideal for working with computations that take a long time to complete; that would benefit from using distributed, parallel frameworks to make them complete faster; and that you’d rather not have ...

Multi-core processors theoretically can run many threads of code in parallel, but some categories of operation currently bog down attempts to raise overall performance by parallelizing computing. Is ...

But the next release of Windows client and server also are going to incorporate changes designed to improve their parallel-processing support. Written by Mary Jo Foley, Senior Contributing Editor ...