August 2015
Intermediate to advanced
286 pages
5h 42m
English
Content preview from Python Parallel Programming CookbookBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Using GPU-accelerated libraries with NumbaPro
NumbaPro provides a Python wrap for CUDA libraries for numerical computing. Each code using these libraries will get a significant speedup without writing any GPU-specific code. The libraries are explained as follows:
- cuBLAS: This is a library developed by NVIDIA that provides the main functions of linear algebra to run on a GPU. Like the Basic Linear Algebra Subprograms (BLAS) library that implements the functions of linear algebra on the CPU, the cuBLAS library classifies its functions into three levels:
- Level 1: Vector operations
- Level 2: Transactions between a matrix and vector
- Level 3: Operations between matrices
The division of these functions in the three levels is based on the number of nested loops ...
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