Intel has announced major updates for its C++ and Fortran tools, updates that are aimed at making it easier for programmers to exploit thread-level and data-level parallelism in multicore processors.

However, the HPC market has the potential to grow much faster than the pool of coders who can do data-parallel programming at the level currently required to wrangle CUDA, CTM, and Cell.

TAKING VECTORIZATION FROM EXTREME TO MAINSTREAM Data-level parallelism, or vectorization, accelerates analytics exponentially by performing the same operation on different sets of data ...

Pipelining and superscalar te chniques both exploit fine-grain instruction-level parallelism — pipelining by temporal means and superscalar by spatial means. Vector processing, in contrast, exploits ...

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.

incorporating intensive thread and data-level parallelism and careful orchestration of data movement. In the grocery analogy, this addresses who will carry each item, can the heavier ones be divided ...

Parallel Domain’s synthetic data platform consists of two modes: training and testing. When training, customers will describe high-level parameters — for example, highway driving with 50% rain ...

A very common method is to use a standard set of directives known as OpenMP, in which the user expresses which sections of the code are to be parallel via a pragma ... because there is no means for ...

enabling two-times 8-way VLIW and up to 14,000 bits of data-level parallelism. It incorporates an advanced, deep pipeline architecture enabling operating speeds of 1.8 GHz at a 7-nm process node ...