Programming on Parallel Machines ; GPU, Multicore, Clusters and More

Abstract

Suitable for either students or professionals. Practical viewpoint:There is very little theoretical analysis of parallel algorithms, such as O() analysis, maximum theoretical speedup, acyclic graphs and so on. Extensive coverage of "wizardry" aspects, i.e. material known to experienced practitioners but generally not in books, such as coverage of loop iteration scheduling, memory effects of storing large arrays and so on. Appendices cover systems background, crucial in applied work but always just "assumed" to be knowledge possessed by the readers