However, the speedup achieved through parallelism is often lower in modern systems. It is no surprise, then, that developers of compilers for data-parallel languages have hypothesized the importance of optimizations that overlap communications with computations in order to reduce execution times and
On the Scalability of Data-Parallel Decomposition Algorithms for Stochastic Programs
โ Scribed by R.J. Qi; S.A. Zenios
- Publisher
- Elsevier Science
- Year
- 1994
- Tongue
- English
- Weight
- 461 KB
- Volume
- 22
- Category
- Article
- ISSN
- 0743-7315
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
## Abstract We describe the Dynamic Distributable Decorrelation Algorithm (DDDA) which efficiently calculates the true statistical error of an expectation value obtained from serially correlated data โonโtheโfly,โ as the calculation progresses. DDDA is an improvement on the FlyvbjergโPetersen renor
The past decade has seen explosive growth in database technology and the amount of data collected. Advances in data collection, use of bar codes in commercial outlets, and the computerization of business transactions have flooded us with lots of data. We have an unprecedented opportunity to analyze