Parallel Programming syllabus
UNIT I PARALLEL PROGRAMMING
Introduction to parallel programming – data parallelism – functional parallelism –pipelining – Flynn’s taxonomy – parallel algorithm design – task/channel model –Foster’s design methodology – case studies: boundary value problem – finding the maximum – n-body problem – Speedup and efficiency – Amdahl’s law – Gustafson- Barsis’s Law – Karp-Flatt Metric – Isoefficiency metric
UNIT II MESSAGE-PASSING PROGRAMMING
The message-passing model – the message-passing interface – MPI standard – basic concepts of MPI: MPI_Init, MPI_Comm_size, MPI_Comm_rank, MPI_Send, MPI_Recv, MPI_Finalize – timing the MPI programs: MPI_Wtime, MPI_Wtick – collective communication: MPI_Reduce, MPI_Barrier, MPI_Bcast, MPI_Gather, MPI_Scatter – case studies: the sieve of Eratosthenes, Floyd’s algorithm, Matrix-vector multiplication
UNIT III SHARED-MEMORY PROGRAMMING
Shared-memory model – OpenMP standard – parallel for loops – parallel for pragma – private variables – critical sections – reductions – parallel loop optimizations – general data parallelism – functional parallelism – case studies: the sieve of Eratosthenes, Floyd’s algorithm, matrix-vector multiplication – distributed shared-memory programming – DSM primitives
UNIT IV PARALLEL ALGORITHMS – I
Monte Carlo methods – parallel random number generators – random number distributions – case studies – Matrix multiplication – rowwise block-stripped algorithm – Cannon’s algorithm – solving linear systems – back substitution – Gaussian elimination – iterative methods – conjugate gradient method
UNIT V PARALLEL ALGORITHMS – II
Sorting algorithms – quicksort – parallel quicksort – hyperquicksort – sorting by regular sampling – Fast fourier transform – combinatorial search – divide and conquer – parallel backtrack search – parallel branch and bound – parallel alpha-beta search.
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