More specifically, this text is ideal for those courses in parallel programming and parallel computing where Java is the preferred language. Parallel programming is an elective course offered within most computer science programs. Parallel programming teaches students how to run programs across several computers, as opposed to running a single program on one computer. One advantage of being able to perform parallel programming is the ability of a computer scientist to test many versions of one problem simultaneously.
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Written by experienced instructor and industry developer Alan Kaminsky, this book addresses techniques for parallel programming on both major categories of parallel computersuSMPs and clusters. Readers gain first-hand experience working with the increasingly popular programming language, Java, as they complete programs from the text written in Java and work with a unique, author-developed Java class library. The book even emphasizes how to use performance metrics in the design of parallel programs, a topic not even addressed in most other texts.
Parallel Computing. Parallel Computers. How to Write Parallel Programs. A First Parallel Program. Part I - Exercises. Massively Parallel Problems. SMP Parallel Programming. Massively Parallel Problems, Part 2. Measuring Speedup. Cache Interference. Measuring Sizeup. Parallel Image File Generation. Load Balancing. Parallel Random Number Generation. Reduction, Part 2. Sequential Dependencies. Barrier Actions. Part II - Exercises. A First Cluster Program.
Parallel Message Passing. Massively Parallel Problems, Part 3. Data Slicing. Load Balancing, Part 2. Measuring Communication Overhead. Reduction, Part 3. Overlapping, Part 2. Part III - Exercises. Massively Parallel Problems, Part 4. Load Balancing, Part 3. Partitioning and Broadcast, Part 2. Parallel Datastore Querying. Part IV - Exercises. MRI Spin Relaxometry.
DNA Sequence Querying. Phylogenetic Tree Construction. Parallel Programming Projects. Numerical Methods. Lock-Free Concurrent Programming.
Building parallel programs : SMPs, clusters, and Java
Parallel programming is an elective course offered within most computer science programs. Because many readers might have previous knowledge of these well-established standards of parallelism, they could benefit from this comparison while studying the PJ approach. Parallel Image File Generation. Having programmed a library that implements parallelism clearly gives pfograms deep insight into the subject.
Building Parallel Programs : SMPs, Clusters and Java