As hardware designers turn toward multicore processors to improve computing power, software programmers must find new programming strategies that harness the power of parallel computing. One technique ...

The addition of multiple cores to microprocessors has created a significant opportunity for parallel programming, but a killer application is needed to push the concept into the mainstream, ...

The tide is changing for analytics architectures. Traditional approaches, from the data warehouse to the data lake, implicitly assume that all relevant data can be stored in a single, centralized ...

Data parallelism is an approach towards parallel processing that depends on being able to break up data between multiple compute units (which could be cores in a processor, processors in a computer, ...

Intel director James Reinders explains the difference between task and data parallelism, and how there is a way around the limits imposed by Amdahl's Law... I'm James Reinders, and I'm going to cover ...

In this Invited Talk from SC16, Tamara Kolda from Sandia presents: Parallel Multiway Methods for Compression of Massive Data and Other Applications. “Scientists are drowning in data. The scientific ...

Hammerspace, the company orchestrating the next data cycle, and Parallel Works, provider of the ACTIVATE control plane for AI and HPC resources, are collaborating on a unified solution for compute and ...

Students will be able to analyze the computing and memory architecture of a super computing node and use OpenMP directives to improve vectorization of their programs. This module focuses on the key ...

The addition of multiple cores to microprocessors has created a significant opportunity for parallel programming, but a killer application is needed to push the concept into the mainstream, ...