Quantitative Analysis
Parallel Processing
Numerical Analysis
C++ Multithreading
Python for Excel
Python Utilities

I. Introduction into GPU programming.
1. What are GPU and CUDA?
2. Selecting GPU.
3. Setting up development environment.
A. Windows notes.
4. Combined use of Cuda, C++ and boost::python.
5. Debugging of boost::python binary using Visual Studio.
6. Debugging of boost::python/Cuda binary using Visual Studio.
7. Using printf in device code.
II. Exception safe dynamic memory handling in Cuda project.
III. Calculation of partial sums in parallel.
IV. Manipulation of piecewise polynomial functions in parallel.
V. Manipulation of localized piecewise polynomial functions in parallel.
Downloads. Index. Contents.

Setting up development environment.

vidia website contains several "getting started" documents. These documents are very helpful. However, one still runs into problems. The section describes some of the problem-solutions that the author encountered.

In any case, if an undocumented problem arises then the first (and often last) thing to do is to execute a search on Nvidia tech-support forum. Beware that people sometimes submit a question without reading existing answers. Hence, if you find your question on the forum and the question is without answer then this is so because this question was answered elsewhere. Simply keep searching.

A. Windows notes.

Downloads. Index. Contents.

Copyright 2007