Using the BSP Cost Model for Optimal Parallel Neural Network Training
نویسنده
چکیده
We derive cost formulae for three diierent parallelisation techniques for training both supervised and unsupervised networks. These formulae are parameterised by properties of the target computer architecture. It is therefore possible to decide both which technique is best for a given parallel computer, and which parallel computer best suits a given technique. One technique, exemplar parallelism, is far superior for almost all parallel computer architectures. Formulae also take into account optimal batch learning as the overall training approach. Cost predictions are made for several of today's popular parallel computers.
منابع مشابه
Using the BSP Cost Model to Optimise Parallel Neural Network Training
We derive cost formulae for three di erent parallelisation techniques for training supervised networks. These formulae are parameterised by properties of the target computer architecture. It is therefore possible to decide the best match between parallel computer and training technique. One technique, exemplar parallelism, is far superior for almost all parallel computer architectures. Formulae...
متن کاملImprove Estimation and Operation of Optimal Power Flow(OPF) Using Bayesian Neural Network
The future of development and design is impossible without study of Power Flow(PF), exigency the system outcomes load growth, necessity add generators, transformers and power lines in power system. The urgency for Optimal Power Flow (OPF) studies, in addition to the items listed for the PF and in order to achieve the objective functions. In this paper has been used cost of generator fuel, acti...
متن کاملA framework for parallel data mining using neural networks
Data mining applications de ne a class of data analysis problems which require powerful computational tools with reasonable execution times. Parallel neural networks present a logical approach to solving these problems. The two most common data mining tasks, classi cation and clustering, can be handled respectively by an appropriate selection of supervised and unsupervised neural network techni...
متن کاملStrategies for Parallelizing Supervised and Unsupervised Learning in Arti cial Neural Networks Using the BSP Cost Model
We use the cost system of BSP (Bulk Synchronous Parallelism) to predict the performance of three di erent parallelization techniques for both supervised and unsupervised learning in arti cial neural networks. We show that exemplar parallelism outperforms techniques that partition the neural network across processors, especially when the number of exemplars is large, typical of applications such...
متن کاملStrategies for Parallelizing Supervised and Unsupervised Learning in Artiicial Neural Networks Using the Bsp Cost Model
We use the cost system of BSP (Bulk Synchronous Parallelism) to predict the performance of three diierent parallelization techniques for both supervised and unsupervised learning in artiicial neural networks. We show that exemplar parallelism outperforms techniques that partition the neural network across processors, especially when the number of exemplars is large, typical of applications such...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1997