Moving from sequential programming to parallel programming, which used to be an area only for niche programmers, was a big jump. In heterogeneous computing, the cores are different. Cores can have the ...

Parallel programming is a technique that allows a program to execute multiple parts of its code simultaneously on different processors or cores. This can improve the performance, efficiency, and ...

Learn how to write clear, reliable, and maintainable code for quantum computers by applying structured programming principles, such as modular design, coding standards, abstraction, and control ...

Recently, I had the good fortune to present a class at the ACM Conference for Computer Science Educators (SIGCSE). While I definitely shared my enthusiasm for parallel programming, I had two key ...

Traditionally, sequential languages have been the norm, though different languages with different programming constructs (i.e., C versus VHDL) have been required to take advantage of multicore ...

Writing a sequential program in an imperative programming language is much easier than writing a distributed algorithm. ... Published in: 2024 IEEE 29th Pacific Rim International Symposium on ...

Abstract: The entire world of parallel computing endured a change when accelerators are gradually embraced in today's high-performance computing cluster. A hybrid CPU-GPU cluster is required to speed ...

Making the transition from sequential to implicit parallel programming: Part 1. Wouldn't it be great if our programs ran twice as fast merely byupgrading our workstation, desktop, server, or embedded ...

We introduce Carol, a refinement-typed programming language for replicated data stores. The salient feature of Carol is that it allows programming and verifying replicated store operations modularly, ...

Learn about sequential vs non-sequential programming, processes, and threads. Explore examples in popular languages like C++, Python, ... The Art of Computer Programming. Raymond's Keynote at PyBay ...