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种子名称:
coursera-heterogeneous-parallel-programming
文件类型:
视频
文件数目:
47个文件
文件大小:
4.57 GB
收录时间:
2016-10-11 10:04
已经下载:
3次
资源热度:
267
最近下载:
2024-12-12 13:03
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coursera-heterogeneous-parallel-programming.torrent
lectures/week1/Heterogeneous Parallel Programming 0.0 1.1 Course Overview.mp4121.4MB
lectures/week1/Heterogeneous Parallel Programming 0.1 1.2 Introduction to Heterogeneous Parallel Computing.mp474.22MB
lectures/week1/Heterogeneous Parallel Programming 0.2 1.3 Portability and Scalability in Heterogeneous Parallel Computing.mp433.28MB
lectures/week1/Heterogeneous Parallel Programming 0.3 1.4 Introduction to CUDA Data Parallelism and Threads.mp4122.68MB
lectures/week1/Heterogeneous Parallel Programming 0.4 1.5 Introduction to CUDA Memory Allocation and Data Movement API.mp4112.62MB
lectures/week1/Heterogeneous Parallel Programming 0.5 1.6 Introduction to CUDA Kernel-Based SPMD Parallel Programming.mp4106.68MB
lectures/week1/Heterogeneous Parallel Programming 0.6 1.7 Kernel-based Parallel Programming Multidimensional Kernel Configuration.mp490.2MB
lectures/week1/Heterogeneous Parallel Programming 0.7 1.8 Kernel-based Parallel Programming Basic Matrix-Matrix Multiplication.mp493.8MB
lectures/week2/Heterogeneous Parallel Programming 1.0 2.1 Kernel-based Parallel Programming - Thread Scheduling.mp4111.83MB
lectures/week2/Heterogeneous Parallel Programming 1.1 2.2 Control Divergence.mp482.61MB
lectures/week2/Heterogeneous Parallel Programming 1.2 2.3 Memory Model and Locality -- CUDA Memories.mp4123.65MB
lectures/week2/Heterogeneous Parallel Programming 1.3 2.4 Tiled Parallel Algorithms.mp4106.83MB
lectures/week2/Heterogeneous Parallel Programming 1.4 2.5 Tiled Matrix Multiplication.mp4119.04MB
lectures/week2/Heterogeneous Parallel Programming 1.5 2.6 Tiled Matrix Multiplication Kernel.mp4170.49MB
lectures/week2/Heterogeneous Parallel Programming 1.6 2.7 Handling Boundary Conditions in Tiling.mp478.8MB
lectures/week2/Heterogeneous Parallel Programming 1.7 2.8 A Tiled Kernel for Arbitrary Matrix Dimensions.mp494.74MB
lectures/week3/Heterogeneous Parallel Programming 2.0 3.1 Performance Considerations - DRAM Bandwidth.mp4120.88MB
lectures/week3/Heterogeneous Parallel Programming 2.1 3.2 Performance Considerations - Memory Coalescing in CUDA.mp484.04MB
lectures/week3/Heterogeneous Parallel Programming 2.2 3.3 Parallel Computation Patterns - Convolution.mp473.94MB
lectures/week3/Heterogeneous Parallel Programming 2.3 3.4 Parallel Computation Patterns - Tiled Convolution.mp491.51MB
lectures/week3/Heterogeneous Parallel Programming 2.4 3.5 Parallel Computation Patterns - 2D Tiled Convolution Kernel.mp491.03MB
lectures/week3/Heterogeneous Parallel Programming 2.5 3.6 Parallel Computation Patterns - Data Reuse in Tiled Convolution.mp4118.46MB
lectures/week4/Heterogeneous Parallel Programming 3.0 4.1 Parallel Computation Patterns - Reduction.mp4126.66MB
lectures/week4/Heterogeneous Parallel Programming 3.1 4.2 Parallel Computation Patterns - A Basic Reduction Kernel.mp496.71MB
lectures/week4/Heterogeneous Parallel Programming 3.2 4.3 Parallel Computation Patterns - A Better Reduction Kernel.mp474.06MB
lectures/week4/Heterogeneous Parallel Programming 3.3 4.4 Parallel Computation Patterns - Scan (Prefix Sum).mp4115.87MB
lectures/week4/Heterogeneous Parallel Programming 3.4 4.5 Parallel Computation Patterns - A Work-Inefficient Scan Kernel.mp4121.77MB
lectures/week4/Heterogeneous Parallel Programming 3.5 4.6 Parallel Computation Patterns - A Work-Efficient Parallel Scan Kernel.mp4124.19MB
lectures/week4/Heterogeneous Parallel Programming 3.6 4.7 Parallel Computation Patterns - More on Parallel Scan.mp4127.16MB
lectures/week5/Heterogeneous Parallel Programming 4.0 5.1 Parallel Computation Patterns - Histogramming.mp458.74MB
lectures/week5/Heterogeneous Parallel Programming 4.1 5.2 Parallel Computation Patterns - Atomic Operations.mp458.21MB
lectures/week5/Heterogeneous Parallel Programming 4.2 5.3 Parallel Computation Patterns - Atomic Operations in CUDA.mp483.67MB
lectures/week5/Heterogeneous Parallel Programming 4.3 5.4 Parallel Computation Patters - Atomic Operations Performance.mp471.91MB
lectures/week5/Heterogeneous Parallel Programming 4.4 5.5 Parallel Computation Patterns - A Privatized Histogram Kernel.mp459.21MB
lectures/week6/Heterogeneous Parallel Programming 5.0 6.1 Efficient Host-Device Data Transfer - Pinned Host Memory.mp4117.61MB
lectures/week6/Heterogeneous Parallel Programming 5.1 6.2 Efficient Host-Device Data Transfer - Task Parallelism in CUDA.mp4113.22MB
lectures/week6/Heterogeneous Parallel Programming 5.2 6.3 Efficient Host-Device Data Transfer - Overlapping Data Transfer with Computation.mp4132.84MB
lectures/week7/Heterogeneous Parallel Programming 6.0 7.1 Related Programming Models - OpenCL Data Parallelism Model.mp484.12MB
lectures/week7/Heterogeneous Parallel Programming 6.1 7.2 Related Programming Models - OpenCL Device Architecture.mp457.7MB
lectures/week7/Heterogeneous Parallel Programming 6.2 7.3 Related Programming Models - OpenCL Host Code Part 1.mp4137.51MB
lectures/week7/Heterogeneous Parallel Programming 6.3 7.4 Related Programming Models - OpenCL Host Code (Cont.).mp478.82MB
lectures/week7/Heterogeneous Parallel Programming 6.4 7.5 Related Programming Models - OpenACC.mp496.91MB
lectures/week7/Heterogeneous Parallel Programming 6.5 7.6 Related Programming Models - OpenACC Details.mp491.11MB
lectures/week8/Heterogeneous Parallel Programming 7.0 8.1 Related Parallel Models - C++ AMP.mp477.92MB
lectures/week8/Heterogeneous Parallel Programming 7.1 8.2 Related Parallel Models - C++ AMP Advance Concepts.mp4108.51MB
lectures/week8/Heterogeneous Parallel Programming 7.2 8.3 Related Parallel Models - Introduction to Heterogeneous Supercomputing and MPI.mp4125.55MB
lectures/week8/Heterogeneous Parallel Programming 7.3 8.4 Conclusions and Future Directions.mp4115.03MB