Big CPU, Big Data: Solving the World's Toughest Computational Problems with Parallel Computing. Questo articolo non è disponibile.Big CPU, Big Data: Solving the World's Toughest Computational Problems with Parallel Computing

In the twenty-first century, scientists and engineers are tackling the world's toughest computational problems with parallel computing. Using multiple processor cores running simultaneously, parallel computers are solving these problems in less time and with greater accuracy than ever before. Even desktop PCs nowadays are powerful parallel computers. To take full advantage of the capabilities of these machines, programmers must learn to write parallel programs.

BIG CPU, BIG DATA teaches you how to write parallel programs for multicore machines, compute clusters, GPU accelerators, and big data map-reduce jobs, in the Java language, with the free, easy-to-use, object-oriented Parallel Java 2 Library. The book also covers how to measure the performance of parallel programs and how to design the programs to run as fast as possible.

With 39 years of industrial and academic computing experience, Alan Kaminsky has been teaching parallel computing since 2004. He is a professor in the Department of Computer Science at the Rochester Institute of Technology.