
“… a thorough, but readable guide to parallel computing—one that can be used by
researchers and students in a wide range of disciplines. … a ‘must-have’ reference
book …”
—David E. Giles, University of Victoria
“This is a book that I will use, both as a reference and for instruction. The examples
are poignant and the presentation moves the reader directly from concept to
working code.”
—Michael Kane, Yale University
Parallel Computing for Data Science: With Examples in R, C++ and CUDA is
one of the rst parallel computing books to concentrate exclusively on parallel data
structures, algorithms, software tools, and applications in data science. It ...