One size does not fit all, and it never will. Parallel programming looks to level the playing field by leveraging multicore hardware.

Programming languages are evolving to bring the software closer to hardware. As hardware architectures become more parallel (with the advent of multicore processors and FPGAs, for example ...

Fortunately the patterns and applications that Programming… relies upon to teach its lessons are fairly common, and as readers explore other material they will find ample opportunity to learn even ...

One of the best features of using FPGAs for a design is the inherent parallelism. Sure, you can write software to take advantage of multiple CPUs. But with an FPGA you can enjoy massive parallelism… ...

"How can quants or financial engineers write financial analytics libraries that can be systematically efficiently deployed on an Intel Xeon Phi co-processor or an Intel Xeon multi-core processor ...

Both parallel programming and asynchronous programming are examples of concurrent programming, meaning more than one operation is running at the same time. Parallel programming is a more specific form ...

Use of a high-level programming model greatly simplifies software development for multicore processors, including heterogeneous multicore devices. Most important, this approach does not sacrifice ...

Parallel programming exploits the capabilities of multicore systems by dividing computational tasks into concurrently executed subtasks. This approach is fundamental to maximising performance and ...

Parallel programming, and OpenACC, is used in high-performance computing in the fields of bioinformatics, quantum chemistry, astrophysics and more. “The model was made to ensure that scientists spend ...