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Heterogeneous Parallel Programming [2014, ENG]

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Heterogeneous Parallel Programming [2014, ENG] (Size: 909.8 MB)
  1 - 1 - 1.1- Course Overview.mp4 25.74 MB
  1 - 1 - 1.1- Course Overview.srt 25.83 KB
  1 - 1 - 1.1- Course Overview.txt 15.82 KB
  1 - 2 - 1.2- Introduction to Heterogeneous Parallel Computing.mp4 17.75 MB
  1 - 2 - 1.2- Introduction to Heterogeneous Parallel Computing.srt 19.44 KB
  1 - 2 - 1.2- Introduction to Heterogeneous Parallel Computing.txt 12.17 KB
  1 - 3 - 1.3- Portability and Scalability in Heterogeneous Parallel Computing.mp4 9.59 MB
  1 - 3 - 1.3- Portability and Scalability in Heterogeneous Parallel Computing.srt 10.85 KB
  1 - 3 - 1.3- Portability and Scalability in Heterogeneous Parallel Computing.txt 6.69 KB
  1 - 4 - 1.4- Introduction to CUDA, Data Parallelism and Threads.mp4 27.09 MB
  1 - 4 - 1.4- Introduction to CUDA, Data Parallelism and Threads.srt 26.47 KB
  1 - 4 - 1.4- Introduction to CUDA, Data Parallelism and Threads.txt 16.05 KB
  1 - 5 - 1.5- Introduction to CUDA, Memory Allocation and Data Movement API.mp4 24.48 MB
  1 - 5 - 1.5- Introduction to CUDA, Memory Allocation and Data Movement API.srt 22.78 KB
  1 - 5 - 1.5- Introduction to CUDA, Memory Allocation and Data Movement API.txt 14.17 KB
  1 - 6 - 1.6- Introduction to CUDA, Kernel-Based SPMD Parallel Programming.mp4 24.23 MB
  1 - 6 - 1.6- Introduction to CUDA, Kernel-Based SPMD Parallel Programming.srt 23.58 KB
  1 - 6 - 1.6- Introduction to CUDA, Kernel-Based SPMD Parallel Programming.txt 14.42 KB
  1 - 7 - 1.7- Kernel-based Parallel Programming, Multidimensional Kernel Configuration.mp4 21.69 MB
  1 - 7 - 1.7- Kernel-based Parallel Programming, Multidimensional Kernel Configuration.srt 19.05 KB
  1 - 7 - 1.7- Kernel-based Parallel Programming, Multidimensional Kernel Configuration.txt 11.67 KB
  1 - 8 - 1.8- Kernel-based Parallel Programming, Basic Matrix-Matrix Multiplication.mp4 21.74 MB
  1 - 8 - 1.8- Kernel-based Parallel Programming, Basic Matrix-Matrix Multiplication.srt 20.23 KB
  1 - 8 - 1.8- Kernel-based Parallel Programming, Basic Matrix-Matrix Multiplication.txt 12.54 KB
  2 - 1 - 2.1- Kernel-based Parallel Programming - Thread Scheduling.mp4 25.53 MB
  2 - 1 - 2.1- Kernel-based Parallel Programming - Thread Scheduling.srt 22.68 KB
  2 - 1 - 2.1- Kernel-based Parallel Programming - Thread Scheduling.txt 13.9 KB
  2 - 2 - 2.2- Control Divergence.mp4 19.83 MB
  2 - 2 - 2.2- Control Divergence.srt 18.11 KB
  2 - 2 - 2.2- Control Divergence.txt 11.25 KB
  2 - 3 - 2.3- Memory Model and Locality -- CUDA Memories.mp4 28.91 MB
  2 - 3 - 2.3- Memory Model and Locality -- CUDA Memories.srt 26.32 KB
  2 - 3 - 2.3- Memory Model and Locality -- CUDA Memories.txt 16.21 KB
  2 - 4 - 2.4- Tiled Parallel Algorithms.mp4 25 MB
  2 - 4 - 2.4- Tiled Parallel Algorithms.srt 23.06 KB
  2 - 4 - 2.4- Tiled Parallel Algorithms.txt 14.24 KB
  2 - 5 - 2.5- Tiled Matrix Multiplication.mp4 25.8 MB
  2 - 5 - 2.5- Tiled Matrix Multiplication.srt 25.03 KB
  2 - 5 - 2.5- Tiled Matrix Multiplication.txt 15.36 KB
  2 - 6 - 2.6- Tiled Matrix Multiplication Kernel.mp4 36.16 MB
  2 - 6 - 2.6- Tiled Matrix Multiplication Kernel.srt 32.79 KB
  2 - 6 - 2.6- Tiled Matrix Multiplication Kernel.txt 20.22 KB
  2 - 7 - 2.7- Handling Boundary Conditions in Tiling.mp4 17.92 MB
  2 - 7 - 2.7- Handling Boundary Conditions in Tiling.srt 16.54 KB
  2 - 7 - 2.7- Handling Boundary Conditions in Tiling.txt 10.19 KB
  2 - 8 - 2.8- A Tiled Kernel for Arbitrary Matrix Dimensions.mp4 21.44 MB
  2 - 8 - 2.8- A Tiled Kernel for Arbitrary Matrix Dimensions.srt 20.43 KB
  2 - 8 - 2.8- A Tiled Kernel for Arbitrary Matrix Dimensions.txt 12.54 KB
  3 - 1 - 3.1- Performance Considerations - DRAM Bandwidth.mp4 29.54 MB
  3 - 1 - 3.1- Performance Considerations - DRAM Bandwidth.srt 28.18 KB
  3 - 1 - 3.1- Performance Considerations - DRAM Bandwidth.txt 17.11 KB
  3 - 2 - 3.2- Performance Considerations - Memory Coalescing in CUDA.mp4 22.72 MB
  3 - 2 - 3.2- Performance Considerations - Memory Coalescing in CUDA.srt 18.42 KB
  3 - 2 - 3.2- Performance Considerations - Memory Coalescing in CUDA.txt 11.42 KB
  3 - 3 - 3.3- Parallel Computation Patterns - Convolution.mp4 21.08 MB
  3 - 3 - 3.3- Parallel Computation Patterns - Convolution.srt 18.67 KB
  3 - 3 - 3.3- Parallel Computation Patterns - Convolution.txt 11.43 KB
  3 - 4 - 3.4- Parallel Computation Patterns - Tiled Convolution.mp4 24.91 MB
  3 - 4 - 3.4- Parallel Computation Patterns - Tiled Convolution.srt 21.07 KB
  3 - 4 - 3.4- Parallel Computation Patterns - Tiled Convolution.txt 13.14 KB
  3 - 5 - 3.5- Parallel Computation Patterns - 2D Tiled Convolution Kernel.mp4 25.29 MB
  3 - 5 - 3.5- Parallel Computation Patterns - 2D Tiled Convolution Kernel.srt 22.77 KB
  3 - 5 - 3.5- Parallel Computation Patterns - 2D Tiled Convolution Kernel.txt 13.96 KB
  3 - 6 - 3.6- Parallel Computation Patterns - Data Reuse in Tiled Convolution.mp4 31.55 MB
  3 - 6 - 3.6- Parallel Computation Patterns - Data Reuse in Tiled Convolution.srt 27.23 KB
  3 - 6 - 3.6- Parallel Computation Patterns - Data Reuse in Tiled Convolution.txt 16.75 KB
  4 - 1 - 4.1- Parallel Computation Patterns - Reduction.mp4 31.08 MB
  4 - 1 - 4.1- Parallel Computation Patterns - Reduction.srt 28.48 KB
  4 - 1 - 4.1- Parallel Computation Patterns - Reduction.txt 17.51 KB
  4 - 2 - 4.2- Parallel Computation Patterns - A Basic Reduction Kernel.mp4 25.07 MB
  4 - 2 - 4.2- Parallel Computation Patterns - A Basic Reduction Kernel.srt 21.87 KB
  4 - 2 - 4.2- Parallel Computation Patterns - A Basic Reduction Kernel.txt 13.26 KB
  4 - 3 - 4.3- Parallel Computation Patterns - A Better Reduction Kernel.mp4 19.99 MB
  4 - 3 - 4.3- Parallel Computation Patterns - A Better Reduction Kernel.srt 18.7 KB
  4 - 3 - 4.3- Parallel Computation Patterns - A Better Reduction Kernel.txt 11.52 KB
  4 - 4 - 4.4- Parallel Computation Patterns - Scan (Prefix Sum).mp4 26.97 MB
  4 - 4 - 4.4- Parallel Computation Patterns - Scan (Prefix Sum).srt 24.08 KB
  4 - 4 - 4.4- Parallel Computation Patterns - Scan (Prefix Sum).txt 14.68 KB
  4 - 5 - 4.5- Parallel Computation Patterns - A Work-Inefficient Scan Kernel.mp4 38.49 MB
  4 - 5 - 4.5- Parallel Computation Patterns - A Work-Inefficient Scan Kernel.srt 26.26 KB
  4 - 5 - 4.5- Parallel Computation Patterns - A Work-Inefficient Scan Kernel.txt 16.08 KB
  4 - 6 - 4.6- Parallel Computation Patterns - A Work-Efficient Parallel Scan Kernel.mp4 37.88 MB
  4 - 6 - 4.6- Parallel Computation Patterns - A Work-Efficient Parallel Scan Kernel.srt 24.5 KB
  4 - 6 - 4.6- Parallel Computation Patterns - A Work-Efficient Parallel Scan Kernel.txt 15.24 KB
  4 - 7 - 4.7- Parallel Computation Patterns - More on Parallel Scan.mp4 39.84 MB
  4 - 7 - 4.7- Parallel Computation Patterns - More on Parallel Scan.srt 25.04 KB
  4 - 7 - 4.7- Parallel Computation Patterns - More on Parallel Scan.txt 15.33 KB
  5 - 1 - 5.1- Parallel Computation Patterns - Histogramming.mp4 22.23 MB
  5 - 1 - 5.1- Parallel Computation Patterns - Histogramming.srt 15.35 KB
  5 - 1 - 5.1- Parallel Computation Patterns - Histogramming.txt 9.37 KB
  5 - 2 - 5.2- Parallel Computation Patterns - Atomic Operations.mp4 22.12 MB
  5 - 2 - 5.2- Parallel Computation Patterns - Atomic Operations.srt 15.33 KB
  5 - 2 - 5.2- Parallel Computation Patterns - Atomic Operations.txt 9.35 KB
  5 - 3 - 5.3- Parallel Computation Patterns - Atomic Operations in CUDA.mp4 30.7 MB
  5 - 3 - 5.3- Parallel Computation Patterns - Atomic Operations in CUDA.srt 21.54 KB
  5 - 3 - 5.3- Parallel Computation Patterns - Atomic Operations in CUDA.txt 13.04 KB
  5 - 4 - 5.4- Parallel Computation Patters - Atomic Operations Performance.mp4 27.71 MB
  5 - 4 - 5.4- Parallel Computation Patters - Atomic Operations Performance.srt 19.55 KB
  5 - 4 - 5.4- Parallel Computation Patters - Atomic Operations Performance.txt 12.07 KB
  5 - 5 - 5.5- Parallel Computation Patterns - A Privatized Histogram Kernel.mp4 23.27 MB
  5 - 5 - 5.5- Parallel Computation Patterns - A Privatized Histogram Kernel.srt 16.84 KB
  5 - 5 - 5.5- Parallel Computation Patterns - A Privatized Histogram Kernel.txt 10.35 KB
  Lecture-3-1-dram-bandwidth.pdf 498.21 KB
  Lecture-3-2-memory-coalescing.pdf 512.64 KB
  Lecture-3-3-convolution.pdf 499.79 KB
  Lecture-3-4-tiled-convolution.pdf 452.39 KB
  Lecture-3-5-2D-convolution-kernel.pdf 477.01 KB
  Lecture-3-6-convolution-reuse.pdf 506.08 KB
  Lecture-4-1-reduction.pdf 294.27 KB
  Lecture-4-2-reduction-kernel.pdf 363.37 KB
  Lecture-4-3-better-reduction-kernel.pdf 413.95 KB
  Lecture-4-4-scan.pdf 526.45 KB
  Lecture-4-5-naive-scan-kernel.pdf 338.76 KB
  Lecture-4-6-work-efficient-scan-kernel.pdf 491.81 KB
  Lecture-4-7-more-on-scan.pdf 579.67 KB
  Lecture-5-1-histogram.pdf 501.85 KB
  Lecture-5-2-atomic-operations.pdf 437.04 KB
  Lecture-5-3-CUDA-atomic.pdf 769.75 KB
  Lecture-5-4-atomic-performance.pdf 443.93 KB
  Lecture-5-5-privatized-histogram.pdf 541.1 KB
  hetero-lecture_slides_002-Lecture 1-Lecture-1-1-Overview.pdf 242.54 KB
  hetero-lecture_slides_002-Lecture 1-Lecture-1-2-heterogeneous.pdf 272.22 KB
  hetero-lecture_slides_002-Lecture 1-Lecture-1-3-software-cost.pdf 279.64 KB
  hetero-lecture_slides_002-Lecture 1-Lecture-1-4-cuda-intro.pdf 593.42 KB
  hetero-lecture_slides_002-Lecture 1-Lecture-1-5-cuda-API.pdf 892.83 KB
  hetero-lecture_slides_002-Lecture 1-Lecture-1-6-cuda-kernel.pdf 490.97 KB
  hetero-lecture_slides_002-Lecture 1-Lecture-1-7-kernel-multidimension.pdf 343.33 KB
  hetero-lecture_slides_002-Lecture 1-Lecture-1-8-kernel-matrix-multiplication.pdf 269.67 KB
  hetero-lecture_slides_002-Lecture 2-Lecture-2-1-transparent-scaling.pdf 430.32 KB
  hetero-lecture_slides_002-Lecture 2-Lecture-2-2-control-divergence.pdf 442.19 KB
  hetero-lecture_slides_002-Lecture 2-Lecture-2-3-cuda-memories.pdf 294.14 KB
  hetero-lecture_slides_002-Lecture 2-Lecture-2-4-tiled-algorithms.pdf 222.14 KB
  hetero-lecture_slides_002-Lecture 2-Lecture-2-5-tiled-matrix-multiplication.pdf 162.42 KB
  hetero-lecture_slides_002-Lecture 2-Lecture-2-6-tiled-kernel.pdf 231.2 KB
  hetero-lecture_slides_002-Lecture 2-Lecture-2-7-boundary-condition.pdf 175.9 KB
  hetero-lecture_slides_002-Lecture 2-Lecture-2-8-boundary-condition-kernel.pdf 233.41 KB
  Гетерогенное параллельное программирование.docx 27.63 KB
  Рекомендуемая литература David B. Kirk, Wen-mei W. Hwu Programming Massively Parallel Processors, Second Edition.pdf 21.4 MB
  ▲ 138 total files

Description


Обучающие видео » Компьютерные видеоуроки и обучающие интерактивные DVD » Программирование (видеоуроки)

Гетерогенное параллельное программирование

Год выпуска: 2014
Производитель: Coursera
Сайт производителя: https://www.coursera.org
Автор: Wen-mei W. Hwu (Иллинойсский университет в Урбане)
Продолжительность: 10,5 часов
Тип раздаваемого материала: Видеоурок
Язык: Английский
Описание: Гетерогенное параллельное программирование
This course introduces concepts, languages, techniques, and patterns for programming heterogeneous, massively parallel processors. Its contents and structure have been significantly revised based on the experience gained from its initial offering in 2012. It covers heterogeneous computing architectures, data-parallel programming models, techniques for memory bandwidth management, and parallel algorithm patterns.

О курсе
All computing systems, from mobile to supercomputers, are becoming heterogeneous, massively parallel computers for higher power efficiency and computation throughput. While the computing community is racing to build tools and libraries to ease the use of these systems, effective and confident use of these systems will always require knowledge about low-level programming in these systems. This course is designed for students to learn the essence of low-level programming interfaces and how to use these interfaces to achieve application goals. CUDA C, with its good balance between user control and verboseness, will serve as the teaching vehicle for the first half of the course. Students will then extend their learning into closely related programming interfaces such as OpenCL, OpenACC, and C++AMP.

The course is unique in that it is application oriented and only introduces the necessary underlying computer science and computer engineering knowledge for understanding. It covers the concept of data parallel execution models, memory models for managing locality, tiling techniques for reducing bandwidth consumption, parallel algorithm patterns, overlapping computation with communication, and a variety of heterogeneous parallel programming interfaces. The concepts learned in this course form a strong foundation for learning other types of parallel programming systems.
[spoiler="Содержание"]
Учебный план курса
• 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.
[/spoiler]
Формат видео: MP4
Видео: MPEG4 Video (H264) 960x540 29.97fps 115kbps [V: h264 main L3.1, yuv420p, 960x540, 115 kb/s
Аудио: AAC 44100Hz stereo 128kbps [A: SoundHandler (aac lc, 44100 Hz, stereo, 128 kb/s)]
[spoiler="Скриншоты"]


[/spoiler]