scholarly journals Power grid simulation applications developed using the GridPACK™ high performance computing framework

2016 ◽  
Vol 141 ◽  
pp. 22-30 ◽  
Author(s):  
Shuangshuang Jin ◽  
Yousu Chen ◽  
Ruisheng Diao ◽  
Zhenyu (Henry) Huang ◽  
William Perkins ◽  
...  
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Power Grid ◽  
Grid Simulation ◽  
Computing Framework ◽  
Performance Computing

scholarly journals High-Performance Computing Framework Based on Distributed Systems for Large-Scale Neurophysiological Data

2021 ◽  
Author(s):  
Mohsen Hadianpour ◽  
Ehsan Rezayat ◽  
Mohammad-Reza Dehaqani
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Large Scale ◽  
Electrophysiological Recording ◽  
Neural Data ◽  
Data Framework ◽  
Neurophysiological Data ◽  
Computing Framework ◽  
Performance Computing ◽  
Neuroscience Community

Abstract Due to the significantly drastic progress and improvement in neurophysiological recording technologies, neuroscientists have faced various complexities dealing with unstructured large-scale neural data. In the neuroscience community, these complexities could create serious bottlenecks in storing, sharing, and processing neural datasets. In this article, we developed a distributed high-performance computing (HPC) framework called `Big neuronal data framework' (BNDF), to overcome these complexities. BNDF is based on open-source big data frameworks, Hadoop and Spark providing a flexible and scalable structure. We examined BNDF on three different large-scale electrophysiological recording datasets from nonhuman primate’s brains. Our results exhibited faster runtimes with scalability due to the distributed nature of BNDF. We compared BNDF results to a widely used platform like MATLAB in an equitable computational resource. Compared with other similar methods, using BNDF provides more than five times faster performance in spike sorting as a usual neuroscience application.

scholarly journals ComputeOps: Container for High Performance Computing

2020 ◽  
Vol 245 ◽  
pp. 07006
Author(s):  
Cécile Cavet ◽  
Martin Souchal ◽  
Sébastien Gadrat ◽  
Gilles Grasseau ◽  
Andrea Satirana ◽  
...  
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Virtual Machines ◽  
Key Concepts ◽  
The Status ◽  
Image Building ◽  
Computing Framework ◽  
Performance Computing ◽  
Linux Containers

The High Performance Computing (HPC) domain aims to optimize code in order to use the latest multicore and parallel technologies including specific processor instructions. In this computing framework, portability and reproducibility are key concepts. A way to handle these requirements is to use Linux containers. These “light virtual machines” allow to encapsulate applications within its environment in Linux processes. Containers have been recently rediscovered due to their abilities to provide both multi-infrastructure environnement for developers and system administrators and reproducibility due to image building file. Two container solutions are emerging: Docker for microservices and Singularity for computing applications. We present here the status of the ComputeOps project which has the goal to study the benefit of containers for HPC applications.

scholarly journals Efficient Communication in Cloud using High Performance Computing System

2019 ◽  
Vol 9 (1) ◽  
pp. 2629-2632
Keyword(s):  
Cloud Computing ◽  
High Performance Computing ◽  
High Performance ◽  
Computing System ◽  
High Performance Computing System ◽  
Efficient Communication ◽  
Previous Decade ◽  
Cloud Framework ◽  
Computing Framework ◽  
Performance Computing

To build the productivity of every errand, we necessitate a framework that should furnish high performance alongside adaptabilities and price effectiveness for client. Cloud computing, since we are for the most part mindful, has turned out to be well known over the previous decade. So as to build up a high performance disseminated framework, we have to use the cloud computing. In this paper, we will initially have a presentation of high performance computing framework. Thusly inspecting them we will investigate inclines in compute and emerald feasible computing to upgrade the routine of a cloud framework. At long last introducing the future degree, we finish up the paper recommending a way to accomplish a emerald high performance cloud framework.

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