Parallel computing for data science : with examples in R, C++ and CUDA
Material type:
Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds |
---|---|---|---|---|---|---|---|
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Main Library Reference | Reference | 005.3 MAT (Browse shelf(Opens below)) | Available | 015461 |
Includes index
Introduction to parallel processing in R --
"Why is my program so slow?": obstacles to speed --
Principles of parallel loop scheduling --
The shared-memory paradigm: a gentle introduction via R --
The shared-memory paradigm: C level --
The shared-memory paradigm : GPUs --
Thrust and Rth --
The message passing paradigm --
MapReduce computation --
Parallel sorting and merging --
Parallel prefix scan --
Parallel matrix operations --
Inherently statistical approaches: subset methods --
Review of matrix algebra --
R quick start --
Introduction to C for R programmers.
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