A Novel Multi-GPU Neural Simulator
نویسندگان
چکیده
Between the biophysical and behavioral studies of the brain lies computational neuroscience. The goal of which, among other things, is to help bridge the gap in our knowledge and provide alternative or complimentary theories to other neurological studies. As more information is provided and more complex theories are developed, the size and computational cost of neural models continues to increase. This is an obvious impediment to the field and something that developers are constantly attempting to overcome. Presented here is a unique simulator design aimed at leveraging advances in hardware for the simulation of biologically realistic neural models. This proof-of-concept design offers an example of a high-performance environment that utilizes multiple general purpose graphical processing units in a novel configuration. The result is a scalable system that offers the promise of both performance and biophysical faithfulness.
منابع مشابه
Intelligent Edge Detection using a CUDA Simulator of Multilayer Neural Network Based on Multi-Valued Neurons
In this paper, we consider the edge detection problem using an intelligent approach. We use a multilayer neural network based on multi-valued neurons (MLMVN) as an intelligent edge enhancer. MLMVN is a complex-valued neural network and it has many advantages over classical neural networks. It significantly outperforms a classical multilayer feedforward neural network in terms of learning speed,...
متن کاملThe efficiency of Artificial Neural Network, Neuro-Fuzzy and Multivariate Regression models for runoff and erosion simulation using rainfall simulator
1- INTRODUCTION According to the complexity of environmental factors related to erosion and runoff, correct simulation of these variables find importance under rain intensity domain of watershed areas. Although modeling of erosion and runoff by Artificial Neural Network and Neuro-Fuzzy based on rainfall-runoff and discharge-sediment models were widely applied by researchers, scrutinizing Arti...
متن کاملA novel CPU/GPU simulation environment for large-scale biologically realistic neural modeling
Computational Neuroscience is an emerging field that provides unique opportunities to study complex brain structures through realistic neural simulations. However, as biological details are added to models, the execution time for the simulation becomes longer. Graphics Processing Units (GPUs) are now being utilized to accelerate simulations due to their ability to perform computations in parall...
متن کاملSpiking Neural P System Simulations on a High Performance GPU Platform
In this paper we present our results in adapting a Spiking Neural P system (SNP system) simulator to a high performance graphics processing unit (GPU) platform. In particular, we extend our simulations to larger and more complex SNP systems using an NVIDIA Tesla C1060 GPU. The C1060 is manufactured for high performance computing and massively parallel computations, matching the maximally parall...
متن کاملHigh performance MRI simulations of motion on multi-GPU systems
BACKGROUND MRI physics simulators have been developed in the past for optimizing imaging protocols and for training purposes. However, these simulators have only addressed motion within a limited scope. The purpose of this study was the incorporation of realistic motion, such as cardiac motion, respiratory motion and flow, within MRI simulations in a high performance multi-GPU environment. ME...
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 2011