[Editor's note: Part 2 of this series shows how to optimize DSP “kernels,” i.e., inner loops. For more programming tips, see the DSP programmer’s guide.] DSP applications typically have tough ...

James Reinders, parallel programming enthusiast Roofline Analysis is a technique that projects a view of realism into optimization targets. It lets us know when we’ve tuned all we can (assuming ...

Discover how to optimize Claude Code for peak efficiency, reduce token usage, and streamline AI workflows with actionable strategies.

This book is very focused on one thing: teaching readers how to develop parallel applications that perform well on NVIDIA’s GPUs using NVIDIA’s CUDA language. The authors do a good job explaining ...

Optimizing Hardware Capacity, Utilizing Automatic Differentiation to Efficiently Compute Derivatives in Parallel Programming Models November 30th, 2022 - By: Technical Paper Link A technical paper ...

By hand optimization of "unrolled" code, it was fairly straightforward to activate the parallel operations available with the SHARC architecture to improve the code speed by another 200%.

Intel's James Reinders looks into the algorithms that form the heart of threading building blocks - a C++ template library for parallel programming.

Facebook researchers say they’ve developed what they call a neural transcompiler, a system that converts code from one high-level programming language like C++, Java, and Python into another.

[Editor's note: Part 2 shows how to optimize DSP kernels (i.e., inner loops), and how to write fast floating-point and fractional code. Part 4 explains why it is important to optimize “control code,” ...