2009 International Workshop on High Performance Computational Systems Biology最新文献

Performance Issues in Evaluating Models and Designing Simulation Algorithms 评估模型和设计仿真算法中的性能问题

2009 International Workshop on High Performance Computational Systems Biology Pub Date : 2009-10-14 DOI: 10.1109/HIBI.2009.16

Roland Ewald, J. Himmelspach, M. Jeschke, Stefan Leye, A. Uhrmacher

{"title":"Performance Issues in Evaluating Models and Designing Simulation Algorithms","authors":"Roland Ewald, J. Himmelspach, M. Jeschke, Stefan Leye, A. Uhrmacher","doi":"10.1109/HIBI.2009.16","DOIUrl":"https://doi.org/10.1109/HIBI.2009.16","url":null,"abstract":"The increase and diversity of simulation methods bears witness of the need for more efficient discrete event simulations in computational biology – but how efficient are those methods, and how to ensure an efficient simulation for a concrete model?As the performance of simulation methods depends on the model, the simulator, and the infrastructure, general answers to those questions are likely to remain illusive; they have to besought individually and experimentally instead. This requires configurable implementations of many algorithms, means to define and conduct meaningful experiments on them, and mechanisms for storing and analyzing observed performance data.In this paper, we first overview basic approaches for improving simulation performance and illustrate the challenges when comparing different methods. We then argue that providing all the aforementioned components in a single tool, in our case the open source modeling and simulation framework JAMES II,reveals many synergies in effectively pursuing both questions.This is exemplified by presenting results of recent studies and introducing a new component to swiftly evaluate simulator code changes against previous experimental data.","PeriodicalId":403061,"journal":{"name":"2009 International Workshop on High Performance Computational Systems Biology","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123363824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

A Parallel Plasma Membrane Simulation 平行质膜模拟

2009 International Workshop on High Performance Computational Systems Biology Pub Date : 2009-10-14 DOI: 10.1109/HIBI.2009.18

P. Burrage, Kevin Burrage, K. Kurowski, Michal T. Lorenc, Dan V. Nicolau, M. Swain, M. Ragan

引用次数: 2

Real-Time Clustering of Datasets with Hardware Embedded Neuromorphic Neural Networks 基于硬件嵌入式神经形态神经网络的数据集实时聚类

2009 International Workshop on High Performance Computational Systems Biology Pub Date : 2009-10-14 DOI: 10.1109/HIBI.2009.24

L. Bakó

{"title":"Real-Time Clustering of Datasets with Hardware Embedded Neuromorphic Neural Networks","authors":"L. Bakó","doi":"10.1109/HIBI.2009.24","DOIUrl":"https://doi.org/10.1109/HIBI.2009.24","url":null,"abstract":"Neuromorphic artificial neural networks attempt to understand the essential computations that take place in the dense networks of interconnected neurons making up the central nervous systems in living creatures. This paper demonstrates that artificial spiking neural networks, – built to resemble the biological model– encoding information in the timing of single spikes are capable of computing and learning clusters from realistic data. It shows how a spiking neural network based on spike-time coding can successfully perform unsupervised and supervised clustering on real-world data. A temporal encoding of continuously valued data is developed. These models are validated through software simulation and then used to develop suitable hardware implementations on FPGA circuits. Fully parallel implementations are investigated and compared with solutions that make use of embedded soft-core microcontrollers to implement some of the most resource-consuming components of the artificial neural network. Details of the implementation are given, with test bench description. Measurement results are presented and compared to related findings in the specific literature.","PeriodicalId":403061,"journal":{"name":"2009 International Workshop on High Performance Computational Systems Biology","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115860912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

The JAMES II Framework for Modeling and Simulation 建模与仿真的JAMES II框架

2009 International Workshop on High Performance Computational Systems Biology Pub Date : 2009-10-14 DOI: 10.1109/HIBI.2009.20

J. Himmelspach, A. Uhrmacher

引用次数: 19

Experimental Analysis of Optimistic Synchronization Algorithms for Parallel Simulation of Reaction-Diffusion Systems 反应扩散系统并行仿真的乐观同步算法实验分析

2009 International Workshop on High Performance Computational Systems Biology Pub Date : 2009-10-14 DOI: 10.1109/HIBI.2009.22

B. Wang, Yiping Yao, Yuliang Zhao, Bonan Hou, Shaoliang Peng

{"title":"Experimental Analysis of Optimistic Synchronization Algorithms for Parallel Simulation of Reaction-Diffusion Systems","authors":"B. Wang, Yiping Yao, Yuliang Zhao, Bonan Hou, Shaoliang Peng","doi":"10.1109/HIBI.2009.22","DOIUrl":"https://doi.org/10.1109/HIBI.2009.22","url":null,"abstract":"With the increasing demands for large-scale and fine-resolution models, simulations of the reaction-diffusion systems are becoming more and more time consuming. Combined with the Stochastic Simulation Method (SSA), the Parallel Discrete-Event Simulation (PDES) is a promising approach to utilize the parallelism in these models. Since synchronization algorithms play the key role in PDES, in this paper, we experimentally investigate the performance and scalability of optimistic synchronization algorithms in simulations of reaction-diffusion systems. First, the Abstract Next Subvolume Method(ANSM), a variant of the Next Subvolume Method (NSM), is presented. It integrates the logical process (LP) based modeling paradigm with several simulation algorithms including both sequential and parallel execution. Second, based on ANSM, three optimistic synchronization algorithms, including a pure optimistic approach, an optimistic approach with risk-free message sending,and a hybrid approach combined the above two are respectively plugged into the simulation. Third, a group of experiments are conducted to study the characteristics of the synchronization algorithms in the parallel simulation of a typical reaction-diffusion systems. The results show that comparing with the pure optimistic approaches, moderate optimistic approaches are more suitable for the stochastic simulation of reaction-diffusion systems, with respect to both the performance and the scalability.","PeriodicalId":403061,"journal":{"name":"2009 International Workshop on High Performance Computational Systems Biology","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126546035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Deployment of a Regularized Feature Selection Framework on an Overlay Desktop Grid 一种正则化特征选择框架在桌面网格上的部署

2009 International Workshop on High Performance Computational Systems Biology Pub Date : 2009-10-14 DOI: 10.1109/HIBI.2009.15

A. Barla, M. Ferrante

引用次数: 1

On the Performances in Simulation of Parallel Databases: An Overview on the Most Recent Techniques for Query Optimization 并行数据库仿真中的性能:查询优化的最新技术综述

2009 International Workshop on High Performance Computational Systems Biology Pub Date : 2009-10-14 DOI: 10.1109/HIBI.2009.25

A. Sadat, P. Lecca

引用次数: 5

The Search for Gene-Gene Interactions in Colorectal Cancer: Using HPC to Overcome Computational Barriers 寻找结直肠癌中基因-基因相互作用:使用HPC克服计算障碍

2009 International Workshop on High Performance Computational Systems Biology Pub Date : 2009-10-14 DOI: 10.1109/HIBI.2009.26

F. Scharinger, Fiona J L Reid, Paul Graham, A. Trew, A. Tenesa, S. Farrington, H. Campbell, M. Dunlop

引用次数: 2

Cellular Level Agent Based Modelling on the Graphics Processing Unit 基于图形处理单元的细胞级代理建模

2009 International Workshop on High Performance Computational Systems Biology Pub Date : 2009-10-14 DOI: 10.1109/HIBI.2009.12

P. Richmond, S. Coakley, D. Romano

引用次数: 31

k-PathA: k-shortest Path Algorithm k-PathA: k最短路径算法

2009 International Workshop on High Performance Computational Systems Biology Pub Date : 2009-10-14 DOI: 10.1109/HIBI.2009.21

Alexander Ullrich, C. Forst

{"title":"k-PathA: k-shortest Path Algorithm","authors":"Alexander Ullrich, C. Forst","doi":"10.1109/HIBI.2009.21","DOIUrl":"https://doi.org/10.1109/HIBI.2009.21","url":null,"abstract":"One important aspect of computational systems biology includes the identification and analysis of functional response networks within large biochemical networks. These functional response networks represent the response of a biological system under a particular experimental condition which can be used to pinpoint critical biological processes.For this purpose, we have developed a novel algorithm to calculate response networks as scored/weighted sub-graphs spanned by k-shortest simple (loop free) paths. The k-shortest simple path algorithm is based on a forward/backward chaining approach synchronized between pairs of processors. The algorithm scales linear with the number of processors used. The algorithm implementation is using a Linux cluster platform, MPI lam and mpiJava messaging as well as the Java language for the application.The algorithm is performed on a hybrid human network consisting of 45,041 nodes and 438,567 interactions together with gene expression information obtained from human cell-lines infected by influenza virus. Its response networks show the early innate immune response and virus triggered processes within human epithelial cells. Especially under the imminent threat of a pandemic caused by novel influenza strains, such as the current H1N1 strain, these analyses are crucial for a comprehensive understanding of molecular processes during early phases of infection. Such a systems level understanding may aid in the identification of therapeutic markers and in drug development for diagnosis and finally prevention of a potentially dangerous disease.","PeriodicalId":403061,"journal":{"name":"2009 International Workshop on High Performance Computational Systems Biology","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131060459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6