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Inicio / Buscador / Ciencias de la Computación / Algoritmos y Estructuras
University of Illinois at Urbana-Champaign vía Coursera
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Heterogeneous Parallel Programming

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  • Week One: Introduction to Heterogeneous Computing, Overview of CUDA C, and Kernel-Based Parallel Programming, with lab tour and programming assignment of vector addition in CUDA C.
  •  Week Two: Memory Model for Locality, Tiling for Conserving Memory Bandwidth, Handling Boundary Conditions, and Performance Considerations, with programming assignment of simple matrix-matrix multiplication in CUDA C.
  • Week Three: Parallel Convolution Pattern, with programming assignment of tiled matrix-matrix multiplication in CUDA C.
  • Week Four: Parallel Scan Pattern, with programming assignment of parallel convolution in CUDA C.
  • Week Five: Parallel Histogram Pattern and Atomic Operations, with programming assignment of parallel scan in CUDA C.
  • Week Six: Data Transfer and Task Parallelism, with programming assignment of parallel histogram in CUDA C.
  • Week Seven: Introduction to OpenCL, Introduction to C++AMP, Introduction to OpenACC, with programming assignment of vector addition using streams in CUDA C.
  • Week Eight: Course Summary, Other Related Programming Models –Thrust, Bolt, and CUDA FORTRAN, with programming assignment of simple matrix-matrix multiplication in choice of OpenCL, C++AMP, or OpenACC.
  • Week Nine: complete any remaining lab assignments, with optional, bonus programming assignments in choice of OpenCL, C++AMP, or OpenACC.