检索结果-内蒙古大学图书馆

25th Annual Computational Neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

BMC NEUROSCIENCE 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

关键词：

来源：评论

学校读者我要写书评

暂无评论

Predoop: Preempting reduce task for job execution accelerations

Predoop: Preempting reduce task for job execution accelerati...

引用

4th and 5th Workshops on Big Data Benchmarks, Performance Optimization, and Emerging Hardware, BPOE 2014

作者： Liang, Yi Wang, Yufeng Fan, Minglu Zhang, Chen Zhu, Yuqing Department of Computer Science Beijing University of Technology Beijing China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy Sciences Beijing China

ISBN: (纸本)9783319130200

Map/Reduce is a popular parallel processing framework for data intensive computing. For overlapping the Map task’s execution phase and the Reduce task’s intermediate data fetching and merging phase, existing Map/ Reduce schedulers always pre-launch the Reduce task at the specific threshold where its map tasks have been launched, and this pattern incurs the occupation of the consuming resources of the reduce task during its idle time on waiting for fetching the intermediate data from map tasks. To address this issue, we propose an extension version of Hadoop map/reduce framework, called Predoop, in this paper. The basic idea of Predoop is to preempt the reduce task during its idle time and allocate the released resource to the map tasks on schedule. To achieve this goal, first, we introduce the preemptive mechanism for reduce tasks and map tasks respectively to enable Map/Reduce tasks to be preempted or resumed with correct status;second, we adopt the preempting-resuming model for the reduce task with the consideration of the progress of Reduce task data fetching & merging and the Map task execution so as to determine the timing of Reduce task preemption and resuming;third, we introduce the preemption-aware task scheduling strategy to allocate the released resources to the on-schedule Map tasks with the consideration of data locality. Experimental result demonstrates that Predoop outperforms Hadoop on various workload and the average job turnaround time can be reduced by maximum of 66.57 %. © Springer International Publishing Switzerland 2014.

关键词： Multitasking

来源：评论

学校读者我要写书评

暂无评论

Dynamic and adaptive calling context encoding

Dynamic and adaptive calling context encoding

引用

12th ACM/IEEE International Symposium on Code Generation and Optimization, CGO 2014

作者： Li, Jianjun Wang, Zhenjiang Wu, Chenggang Hsu, Wei-Chung Xu, Di State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China Department of Computer Science National Taiwan University Taipei Taiwan IBM Research-China Beijing China

ISBN: (纸本)9781450326704

Calling context has been widely used in many software development processes such as testing, event logging, and program analysis. It plays an even more important role in data race detection and performance bottleneck analysis for multi-threaded programs. This paper presents DACCE (Dynamic and Adaptive Calling Context Encoding), an efficient runtime encoding/decoding mechanism for singlethreaded and multi-threaded programs that captures dynamic calling contexts. It can dynamically encode all call paths invoked at runtime, and adjust the encodings according to program's execution behavior. In contrast to existing context encoding method, DACCE can work on incomplete call graph, and it does not require source code analysis and offline profiling to conduct context encoding. DACCE has significantly expanded the functionality and applicability of calling context with even lower runtime overhead. DACCE is very efficient based on experiments with SPEC CPU2006 and Parsec 2.1 (with about 2% of runtime overhead) and effective for all tested benchmarks. Copyright © 2014 by the Association for computing Machinery, Inc. (ACM).

关键词： Encoding (symbols)

来源：评论

学校读者我要写书评

暂无评论

BPM/BPM+: Software-based dynamic memory partitioning mechanisms for mitigating dram bank-/channel-level interferences in multicore systems

BPM/BPM+: Software-based dynamic memory partitioning mechani...

引用

作者： Liu, Lei Cui, Zehan Li, Yong Bao, Yungang Chen, Mingyu Wu, Chengyong State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China Graduate School CAS China Department of ECE University of Pittsburgh United States

The main memory system is a shared resource in modern multicore machines that can result in serious interference leading to reduced throughput and unfairness. Many new memory scheduling mechanisms have been proposed to address the interference problem. However, these mechanisms usually employ relative complex scheduling logic and need modifications to Memory Controllers (MCs), which incur expensive hardware design and manufacturing overheads. This article presents a practical software approach to effectively eliminate the interference without any hardware modifications. The key idea is to modify the OS memory management system and adopt a page-coloring-based Bank-level Partitioning Mechanism (BPM) that allocates dedicated DRAM banks to each core (or thread). By using BPM, memory requests from distinct programs are segregated across multiple memory banks to promote locality/fairness and reduce interference. We further extend BPM to BPM+ by incorporating channel-level partitioning, on which we demonstrate additional gain over BPM in many cases. To achieve benefits in the presence of diverse application memory needs and avoid performance degradation due to resource underutilization, we propose a dynamic mechanism upon BPM/BPM+ that assigns appropriate bank/channel resources based on application memory/bandwidth demands monitored through PMU (performance- monitoring unit) and a low-overhead OS page table scanning process. We implement BPM/BPM+ in Linux 2.6.32.15 kernel and evaluate the technique on four-core and eight-core real machines by running a large amount of randomly generated multiprogrammed and multithreaded workloads. Experimental results show that BPM/BPM+ can improve the overall system throughput by 4.7%/5.9%, on average, (up to 8.6%/9.5%) and reduce the unfairness by an average of 4.2%/6.1% (up to 15.8%/13.9%). © 2014 ACM.

关键词： Scheduling

来源：评论

学校读者我要写书评

暂无评论

BDGS: A scalable big data generator suite in big data benchmarking

BDGS: A scalable big data generator suite in big data benchm...

引用

2013 Workshop Series on Big Data Benchmarking, WBDB.cn and WBDB.us.

作者： Ming, Zijian Luo, Chunjie Gao, Wanling Han, Rui Yang, Qiang Wang, Lei Zhan, Jianfeng State Key Laboratory Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Department of Computing Imperial College London London United Kingdom

ISBN: (纸本)9783319105956

Data generation is a key issue in big data benchmarking that aims to generate application-specific data sets to meet the 4V requirements of big data. Specifically, big data generators need to generate scalable data (Volume) of different types (Variety) under controllable generation rates (Velocity) while keeping the important characteristics of raw data (Veracity). This gives rise to various new challenges about how we design generators efficiently and successfully. To date, most existing techniques can only generate limited types of data and support specific big data systems such as Hadoop. Hence we develop a tool, called Big Data Generator Suite (BDGS), to efficiently generate scalable big data while employing data models derived from real data to preserve data veracity. The effectiveness of BDGS is demonstrated by developing six data generators covering three representative data types (structured, semi-structured and unstructured) and three data sources (text, graph, and table data). © Springer International Publishing Switzerland 2014.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

Parallel optimization of geometric correction algorithm based on CPU-GPU hybrid architecture

Parallel optimization of geometric correction algorithm base...

引用

International Conference on Vehicle and Mechanical Engineering and Information technology, VMEIT 2014

作者： Bai, Hong Tao Li, Yu Gang Chen, Li Ying Wang, Yan Ling Beijing Lab of Intelligent Information Technology School of Computer Science Beijing Institute of Technology Beijing 100081 China Beijing Lab of Intelligent Information Technology School of Computer Science Beijing Institute of Technology Beijing China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783038350606

Geometric correction is an essential processing procedure in remote sensing image processing. The algorithms used in geometric correction are time intensive and the size of remote sensing images is very large. Meanwhile, the data to be calculated is in huge size and is accumulating rapidly every day. Hence, the fast processing of geometric correction of remote sensing image becomes an urgent research problem. Through the rapid development of GPU, the current GPU has a great advantage in processing speed and memory bandwidth over CPU. It provides a new way for high performance computing. In this paper, we present three optimization solutions based on CPU-GPU hybrid architecture and the analysis of their performances. Experiments are also given and the results are consistent with the analysis. © (2014) Trans Tech Publications, Switzerland.

关键词： Graphics processing unit

来源：评论

学校读者我要写书评

暂无评论

Test and repair flow for shared BISR in asynchronous multi-processors

Test and repair flow for shared BISR in asynchronous multi-p...

引用

20th IEEE International Symposium on Asynchronous Circuits and systems, ASYNC 2014

作者： Wang, Gang Wang, Xu Chen, Xinke Xue, Shuangbai Key Laboratory of Computer System and Architecture Chinese Academy of Sciences Beijing 100190 China Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Loongson Technology Corporation Limited Beijing 100190 China Shandong Eway Information and Technology Co. Ltd China

ISBN: (纸本)9781479937899

We present a hierarchical test and repair flow for shared BISR (Built-In Self-Repair) in asynchronous multi-processors. The flow partitions the memories local to a processor in groups and treats the groups as a whole when doing the repair. The flow runs automatically with few interventions except at the beginning stage. It can be used effectively for practical industrial test and repair. Its test time is as good as equivalent to that of parallel BISR, while its test power is substantially lower, about 40% that of parallel repair. It also has a superior repair rate, about 11-12% better compared to sequential and parallel BISR. © 2014 IEEE.

关键词： Repair

来源：评论

学校读者我要写书评

暂无评论

Concurrency bug localization using shared memory access pairs 14

Concurrency bug localization using shared memory access pair...

引用

2014 19th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2014

作者： Wang, Wenwen Wu, Chenggang Yew, Pen-Chung Yuan, Xiang Wang, Zhenjiang Li, Jianjun Feng, Xiaobing State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China University of Chinese Academy of Sciences Beijing China Department of Computer Science and Engineering University of Minnesota at Twin-Cities United States

ISBN: (纸本)9781450326568

Non-determinism in concurrent programs makes their debugging much more challenging than that in sequential programs. To mitigate such difficulties, we propose a new technique to automatically locate buggy shared memory accesses that triggered concurrency bugs. Compared to existing fault localization techniques that are based on empirical statistical approaches, this technique has two advantages. First, as long as enough successful runs of a concurrent program are collected, the proposed technique can locate buggy memory accesses to the shared data even with only one single failed run captured, as opposed to the need of capturing multiple failed runs in other statistical approaches. Second, the proposed technique is more precise because it considers memory accesses in those failed runs that terminate prematurely.

关键词： Program debugging

来源：评论

学校读者我要写书评

暂无评论

Concurrency bug localization using shared memory access pairs

Concurrency bug localization using shared memory access pair...

引用

关键词： Memory architecture

来源：评论

学校读者我要写书评

暂无评论

The implications of diverse applications and scalable data sets in benchmarking big data systems

The implications of diverse applications and scalable data s...

引用

2nd Workshop on Specifying Big Data Benchmarks, WBDB 2012

作者： Jia, Zhen Zhou, Runlin Zhu, Chunge Wang, Lei Gao, Wanling Shi, Yingjie Zhan, Jianfeng Zhang, Lixin State Key Laboratory Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China University of Chinese Academy of Sciences China National Computer Network Emergency Response Technical Team Coordination Center of China China

ISBN: (纸本)9783642539732

Now we live in an era of big data, and big data applications are becoming more and more pervasive. How to benchmark data center computer systems running big data applications (in short big data systems) is a hot topic. In this paper, we focus on measuring the performance impacts of diverse applications and scalable volumes of data sets on big data systems. For four typical data analysis applications - an important class of big data applications, we find two major results through experiments: first, the data scale has a significant impact on the performance of big data systems, so we must provide scalable volumes of data sets in big data benchmarks. Second, for the four applications, even all of them use the simple algorithms, the performance trends are different with increasing data scales, and hence we must consider not only variety of data sets but also variety of applications in benchmarking big data systems. © 2014 Springer-Verlag Berlin Heidelberg.

关键词： Benchmarking

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：