We describe NIMBLE, a system for programming statistical algorithms for\ngeneral model structures within R. NIMBLE is designed to meet three challenges:\nflexible model specification, a language for programming algorithms that can\nuse different models, and a balance between high-level programmability ...
Programming models embody concepts and offer tools that support developers in building large computational systems. A distributed programming model, in particular, facilitates translating sequential algorithms into distributed programs that can execute over distributed systems. The model's design determines ho...
Int J Parallel Prog (2018) 46:505–507 https://doi.org/10.1007/s10766-017-0531-0 EDITORIAL Guest Editorial for Programming Models and Algorithms for Data Analysis in HPC Systems Salvatore Cuomo1 · Marco Aldinucci2 · Massimo Torquati3 Published online: 7 October 2017 © Springer Science+...
VPI implements computer vision and image processing algorithms on computing engines such as CPUs, GPUs, PVA, and VIC.
You can apply this technique to your own problems and data models, too. You should see sensible speedups as long as you can rewrite your algorithms in a “divide and conquer” fashion that is free of I/O work and locking. Acknowledgements The author would like to thank Brian Goetz and Mi...
people started trying to write memory models defining what a high-level programming language like Java or C++ guarantees to programmers writing code in that language. Including the compiler in the model makes the job of defining a reasonable model much more complicated. 最初,内存模型的目标是定义编...
While the resulting partitions of static algorithms do not change in all executions, those of dynamic algorithms could be updated before each execution to adapt to environmental conditions and optimize offloading objectives. Because of that, dynamic algorithms may have high overhead during the ...
Because of the characteristics of irregular algorithms, efficient parallel implementations are difficult to achieve since the distribution of work and data cannot be determined a priori. However, suitable parallel programming models and libraries for structuring, scheduling, load balancing, coordination, and...
patterns algorithms gpu constexpr modern-cpp cuda printf cpp11 utility-library cuda-kernels gpu-programming cuda-library elegant-coding cuda-programming utility-functions printf-functions Updated Apr 24, 2022 Cuda MuGdxy / muda Star 172 Code Issues Pull requests μ-Cuda, COVER THE LAST MILE OF...
Due to its high performance, Java is a suitable language for developing ETL jobs and performing data tasks that require big storage and complex processing requirements, like machine learning algorithms. 5. Julia Julia can be considered a data science rising star. Despite being one of the youngest...