Another key step to implement a parallel algorithm on a GPU is to write and optimize your kernel code. A kernel is a function that runs on the GPU and performs the main computation of your algorithm.

intro: This repo contains the source code for k-means GPU acceleration project. This project aims to implement GPU acceleraion (using 3 methods) on the algorithm, and compare the results. objectives: ...

GPU implementation of Gillespie's Stochastic Simulation Algorithm (GSSA) using CUDA. - tantrev/cuda-gssa. ... presents the general user workflow in a standard flowchart. Figure 1(b) shows the core ...

Abstract: Universal combinatorics coding is a new kind of coding method and whole ordinal plays an important role in universal combinatorics coding. Whole ordinal GPU parallel algorithm is proposed in ...

There are different types of flowchart symbols and conventions, such as ANSI, ISO, or UML, that you can use to document your algorithm. You should choose a standard notation that is consistent ...

The algorithm was specifically designed to take advantage of the high GPU bandwidth and runs well on both OpenCL 1.2 (Intel® HD Graphics 4600) and OpenCL 2.0 drivers (Intel® HD Graphics 4600 and ...

Computational chemists working on Gaussian and GAMESS and other quantum chemistry code development who are interested in achieving top performance from GPUs in diverse applications using Monte Carlo ...