The resulting benefit can vary accordingly. “A small simple branch predictor might speed up a processor by 15%, whereas a ...

This article is this edition's winner of the ASU Writing Competition. The competition is open quarterly to current ASU ...

The article illustrates techniques for generating parallel logic outputs with industrial serialized digital inputs.

The United States Data Security Program (DSP) represents a significant regulatory undertaking by the US government to control the flow of bulk sensitive data to specific foreign countries, for ...

In this RFC we are talking about request-level parallelism for this. EP is Expert Parallelism for MoEs, where experts are distributed across EP ranks, and tokens are dispatched to the GPUs holding the ...

Hammerspace's David Flynn talks with theCUBE about developing a parallel NFS architecture that could revolutionize data storage.

PySpark: deployed as the engine for distributed computing, optimizes computational efficiency in ETL processes by distributing data across multiple nodes for parallel processing, scaling to match ...

Support multi-process, multi-threaded, and NoGIL multi-threaded based parallelism at the node level Some users may not want to move to multi-threading, may be stuck with GIL Python, or non-thread-safe ...

CPUs also have a limited ability to exploit instruction-level parallelism based on CPU width and data dependencies. These CPU performance bottlenecks are real, pervasive, and not easily resolved.