International Neuroscience Initiatives through the Lens of High-Performance Computing

Bouchard, Kristofer E.; Aimone, James B.; Chun, Miyoung; Dean, Thomas; Denker, Michael; Diesmann, Markus; Donofrio, David D.; Frank, Loren M.; Kasthuri, Narayanan; Koch, Christof; Rubel, Oliver; Simon, Horst D.; Sommer, F. T.; Prabhat, .

doi:10.1109/MC.2018.2141039

Title: International Neuroscience Initiatives through the Lens of High-Performance Computing

Full Record
Other Related Research

Abstract

Neuroscience initiatives aim to develop new technologies and tools to measure and manipulate neuronal circuits. In this paper, to deal with the massive amounts of data generated by these tools, the authors envision the co-location of open data repositories in standardized formats together with high-performance computing hardware utilizing open source optimized analysis codes.

Authors:

Bouchard, Kristofer E. ^[1]; Aimone, James B. ^[2]; Chun, Miyoung ^[3]; Dean, Thomas ^[4]; Denker, Michael ^[5]; Diesmann, Markus ^[6]; Donofrio, David D. ^[7]; Frank, Loren M. ^[8]; Kasthuri, Narayanan ^[9]; Koch, Christof ^[10]; Rubel, Oliver ^[11]; Simon, Horst D. ^[12]; Sommer, F. T. ^[13]; Prabhat, . ^[14]

Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Neural Systems and Engineering Lab.; Univ. of California, Berkeley, CA (United States). Helen Wills Neuroscience Inst.
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Center for Computing Research
Kavli Foundation, Los Angeles, CA (United States)
Google, Mountain View, CA (United States); Stanford Univ., CA (United States)
Forschungszentrum Julich (Germany). Inst. of Neuroscience and Medicine (INM-6). Computational and Systems Neuroscience
Forschungszentrum Julich (Germany). Inst. of Neuroscience and Medicine (INM-6). Computational and Systems Neuroscience. Inst. for Advanced Simulation (IAS-6). Theoretical Neuroscience
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computer Architecture Group
Univ. of California, San Francisco, CA (United States). Dept. of Physiology. Howard Hughes Medical Inst.
Argonne National Lab. (ANL), Argonne, IL (United States); Univ. of Chicago, IL (United States). Dept. of Neurobiology
Allen Inst. for Brain Science, Seattle, WA (United States)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Univ. of California, Berkeley, CA (United States). Redwood Center for Theoretical Neuroscience. Helen Wills Neuroscience Inst.
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center

Publication Date:: Fri Apr 27 00:00:00 EDT 2018

Research Org.:: Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

Sponsoring Org.:: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)

OSTI Identifier:: 1461981

Grant/Contract Number:: AC02-05CH11231

Resource Type:: Accepted Manuscript

Journal Name:: Computer

Additional Journal Information:: Journal Volume: 51; Journal Issue: 4; Journal ID: ISSN 0018-9162

Publisher:: IEEE

Country of Publication:: United States

Language:: English

Subject:: 97 MATHEMATICS AND COMPUTING; 60 APPLIED LIFE SCIENCES; neuroscience; neuroscience initiatives; brain; high performance computing; HPC; data; data analysis; scientific computing

Citation Formats


                    Bouchard, Kristofer E., Aimone, James B., Chun, Miyoung, Dean, Thomas, Denker, Michael, Diesmann, Markus, Donofrio, David D., Frank, Loren M., Kasthuri, Narayanan, Koch, Christof, Rubel, Oliver, Simon, Horst D., Sommer, F. T., and Prabhat, . International Neuroscience Initiatives through the Lens of High-Performance Computing.  United States: N. p., 2018. 
Web.  doi:10.1109/MC.2018.2141039.

Copy to clipboard


                    Bouchard, Kristofer E., Aimone, James B., Chun, Miyoung, Dean, Thomas, Denker, Michael, Diesmann, Markus, Donofrio, David D., Frank, Loren M., Kasthuri, Narayanan, Koch, Christof, Rubel, Oliver, Simon, Horst D., Sommer, F. T., & Prabhat, . International Neuroscience Initiatives through the Lens of High-Performance Computing.  United States.  https://doi.org/10.1109/MC.2018.2141039

Copy to clipboard


                    Bouchard, Kristofer E., Aimone, James B., Chun, Miyoung, Dean, Thomas, Denker, Michael, Diesmann, Markus, Donofrio, David D., Frank, Loren M., Kasthuri, Narayanan, Koch, Christof, Rubel, Oliver, Simon, Horst D., Sommer, F. T., and Prabhat, . Fri .  
"International Neuroscience Initiatives through the Lens of High-Performance Computing".  United States.  https://doi.org/10.1109/MC.2018.2141039.  https://www.osti.gov/servlets/purl/1461981.

Copy to clipboard


                    
@article{osti_1461981,

  title        = {International Neuroscience Initiatives through the Lens of High-Performance Computing},

  author       = {Bouchard, Kristofer E. and Aimone, James B. and Chun, Miyoung and Dean, Thomas and Denker, Michael and Diesmann, Markus and Donofrio, David D. and Frank, Loren M. and Kasthuri, Narayanan and Koch, Christof and Rubel, Oliver and Simon, Horst D. and Sommer, F. T. and Prabhat, .},

  abstractNote = {Neuroscience initiatives aim to develop new technologies and tools to measure and manipulate neuronal circuits. In this paper, to deal with the massive amounts of data generated by these tools, the authors envision the co-location of open data repositories in standardized formats together with high-performance computing hardware utilizing open source optimized analysis codes.},

  doi          = {10.1109/MC.2018.2141039},

  journal      = {Computer},

  number       = 4,

  volume       = 51,

  place        = {United States},

  year         = {Fri Apr 27 00:00:00 EDT 2018},

  month        = {Fri Apr 27 00:00:00 EDT 2018}

}

Copy to clipboard

Journal Article:

Free Publicly Available Full Text

Accepted Manuscript (DOE)

Publisher's Version of Record

https://doi.org/10.1109/MC.2018.2141039

Other availability

Search WorldCat to find libraries that may hold this journal

Save / Share:

Export Metadata

Save to My Library

Similar Records in DOE PAGES and OSTI.GOV collections:

Editorial: Neuroscience, computing, performance, and benchmarks: Why it matters to neuroscience how fast we can compute

Journal Article Aimone, James B. ; Awile, Omar ; Diesmann, Markus ; ... - Frontiers in Neuroinformatics

At the turn of the millennium the computational neuroscience community realized that neuroscience was in a software crisis: software development was no longer progressing as expected and reproducibility declined. The International Neuroinformatics Coordinating Facility (INCF) was inaugurated in 2007 as an initiative to improve this situation. The INCF has since pursued its mission to help the development of standards and best practices. In a community paper published this very same year, Brette et al. tried to assess the state of the field and to establish a scientific approach to simulation technology, addressing foundational topics, such as which simulation schemes aremore »« less
https://doi.org/10.3389/fninf.2023.1157418

Full Text Available
Infrastructure for Multiphysics Software Integration in High Performance Computing-Aided Science and Engineering

Technical Report Campbell, Michael T. ; Safdari, Masoud ; Kress, Jessica E. ; ...

The project described in this report constructed and exercised an innovative multiphysics coupling toolkit called the Illinois Rocstar MultiPhysics Application Coupling Toolkit (IMPACT). IMPACT is an open source, flexible, natively parallel infrastructure for coupling multiple uniphysics simulation codes into multiphysics computational systems. IMPACT works with codes written in several high-performance-computing (HPC) programming languages, and is designed from the beginning for HPC multiphysics code development. It is designed to be minimally invasive to the individual physics codes being integrated, and has few requirements on those physics codes for integration. The goal of IMPACT is to provide the support needed to enablemore »« less
https://doi.org/10.2172/1329929

Full Text Available
Automated Cache Performance Analysis And Optimization

Technical Report Mohror, Kathryn

While there is no lack of performance counter tools for coarse-grained measurement of cache activity, there is a critical lack of tools for relating data layout to cache behavior to application performance. Generally, any nontrivial optimizations are either not done at all, or are done ”by hand” requiring significant time and expertise. To the best of our knowledge no tool available to users measures the latency of memory reference instructions for particular addresses and makes this information available to users in an easy-to-use and intuitive way. In this project, we worked to enable the Open|SpeedShop performance analysis tool to gathermore »« less
https://doi.org/10.2172/1113233

Full Text Available
Data Locality Enhancement of Dynamic Simulations for Exascale Computing (Final Report)

Technical Report Shen, Xipeng

The development of modern processors exhibits two trends that complicate the optimizations of modern software. The first is the increasing sensitivity of processors' throughput to irregularities in computation. With more processors produced through a massive integration of simple cores, future systems will increasingly favor regular data-level parallel computations, but deviate from the needs of applications with complex patterns. Some evidences are already shown on Graphic Processing Units (GPU): Irregular data accesses (e.g., indirect references A[D[i]]) and conditional branches are limiting many GPU applications' performance at a level an order of magnitude lower than the peak of GPU. The second hardwaremore »« less
https://doi.org/10.2172/1576175

Full Text Available
Performance Analysis of PIConGPU: Particle-in-Cell on GPUs using NVIDIA’s NSight Systems and NSight Compute

Technical Report Leinhauser, Matthew ; Young, Jeffrey ; Bastrakov, Sergei ; ...

PIConGPU, Particle In Cell on GPUs, is an open source simulations framework for plasma and laser-plasma physics used to develop advanced particle accelerators for radiation therapy of cancer, high energy physics and photon science. While PIConGPU has been optimized for at least 5 years to run well on NVIDIA GPU-based clusters, there has been limited exploration by the development team of potential scalability bottlenecks using recently updated and new tools including NVIDIA’s NVProf tool and the brand-new NVIDIA NSight Suite (Systems and Compute) tools. PIConGPU is a highly optimized application that runs production jobs at scale on a system Oakmore »« less
https://doi.org/10.2172/1761619

Full Text Available

Similar Records