Algorithmic GPGPU Memory Optimization
نویسندگان
چکیده
منابع مشابه
A framework for computation-memory algorithmic optimization for signal processing
The heterogeneity of today’s computing environment means computation-intensive signal processing algorithms must be optimized for performance in a machine dependent fashion. In this paper, we present a dynamic memory model and associated optimization framework that finds a machine-dependent, near-optimal implementation of an algorithm by exploiting the computation-memory tradeoff. By optimal, w...
متن کاملmemCUDA: Map Device Memory to Host Memory on GPGPU Platform
The Compute Unified Device Architecture (CUDA) programming environment from NVIDIA is a milestone towards making programming many-core GPUs more flexible to programmers. However, there are still many challenges for programmers when using CUDA. One is how to deal with GPU device memory, and data transfer between host memory and GPU device memory explicitly. In this study, source-to-source compil...
متن کاملTowards Heuristic Algorithmic Memory
We propose a long-term memory design for artificial general intelligence based on Solomonoff’s incremental machine learning methods. We introduce four synergistic update algorithms that use a Stochastic Context-Free Grammar as a guiding probability distribution of programs. The update algorithms accomplish adjusting production probabilities, re-using previous solutions, learning programming idi...
متن کاملAlgorithmic Congestion Optimization
Nowadays, many cities or urban areas, say San Francisco Bay Area, started to converge into a divided “working area” “living area” layout, where people commute daily to working area on mornings and commute back on nights. The commute usually depend on few vital highways. For example, the ”working area” could be San Francisco inner city, and living area could be east bay or south bay, and the vit...
متن کاملAlgorithmic Techniques for Geometric Optimization
We review the recent progress in the design of e cient algorithms for various problems in geometric optimization. The emphasis in this survey is on the techniques used to attack these problems, such as parametric searching, geometric alternatives to parametric searching, prune-and-search techniques for linear programming and related problems, and LP-type problems and their e cient solution.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: JSTS:Journal of Semiconductor Technology and Science
سال: 2014
ISSN: 1598-1657
DOI: 10.5573/jsts.2014.14.4.391