Principles of parallel programming
With the rise of multi-core architecture, parallel programming is an increasingly important topic for software engineers and computer system designers. Written by well-known researchers Larry Snyder and Calvin Lin, this highly anticipated first edition emphasizes the principles underlying parallel computation, explains the various phenomena, and clarifies why these phenomena represent opportunities or barriers to successful parallel programming. Ideal for an advanced upper-level undergraduate course, Principles of Parallel Programmingsupplies enduring knowledge that will outlive the current hardware and software, aiming to inspire future researchers to build tomorrow's solutions.
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Examining Sequential and Parallel
Parallelism Using Multiple Instruction
28 other sections not shown
abstractions address space algorithm allocation Amdahl's Law approach assigned atomic barrier block BlueGene/L buffer cache Chapter Co-Array Fortran Code Spec compiler complete concurrency condition variables count critical section data structure deadlock define dependences dimension distributed dynamically elements example execution false sharing function GPUs granularity grid hardware implement increase initialize integer interactions interface iteration Java latency locality lock loop machine MapReduce matrix message passing monitor MPI Comm MPI error code MPI_COMM_WORLD MPI_FLOAT multi-core multi-core chip multiple mutex NESL non-local number of processors number of threads OpenMP operand operations overhead parallel computation parallel programming Peril-L POSIX Threads pragma problem produce pthread_mutex_lock(Slock queue race conditions reduce and scan references region remap result Return value routine sequence sequential program shared memory shown in Figure single specified speedup statement successive over-relaxation synchronization tally thread ID tion tree Unified Parallel void wait write ZPL's