scholarly journals Dynamic monitoring of high-performance distributed applications

2003 ◽  
Author(s):  
D. Gunter ◽  
B. Tierney ◽  
K. Jackson ◽  
J. Lee ◽  
M. Stoufer
Keyword(s):  
High Performance ◽  
Distributed Applications ◽  
Dynamic Monitoring

scholarly journals Computational storage: an efficient and scalable platform for big data and HPC applications

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Mahdi Torabzadehkashi ◽  
Siavash Rezaei ◽  
Ali HeydariGorji ◽  
Hosein Bobarshad ◽  
Vladimir Alves ◽  
...  
Keyword(s):  
Big Data ◽  
High Performance ◽  
Distributed Processing ◽  
Data Access ◽  
Distributed Applications ◽  
Process Data ◽  
Storage Devices ◽  
Hadoop Mapreduce ◽  
Big Data Applications ◽  
Application Processor

AbstractIn the era of big data applications, the demand for more sophisticated data centers and high-performance data processing mechanisms is increasing drastically. Data are originally stored in storage systems. To process data, application servers need to fetch them from storage devices, which imposes the cost of moving data to the system. This cost has a direct relation with the distance of processing engines from the data. This is the key motivation for the emergence of distributed processing platforms such as Hadoop, which move process closer to data. Computational storage devices (CSDs) push the “move process to data” paradigm to its ultimate boundaries by deploying embedded processing engines inside storage devices to process data. In this paper, we introduce Catalina, an efficient and flexible computational storage platform, that provides a seamless environment to process data in-place. Catalina is the first CSD equipped with a dedicated application processor running a full-fledged operating system that provides filesystem-level data access for the applications. Thus, a vast spectrum of applications can be ported for running on Catalina CSDs. Due to these unique features, to the best of our knowledge, Catalina CSD is the only in-storage processing platform that can be seamlessly deployed in clusters to run distributed applications such as Hadoop MapReduce and HPC applications in-place without any modifications on the underlying distributed processing framework. For the proof of concept, we build a fully functional Catalina prototype and a CSD-equipped platform using 16 Catalina CSDs to run Intel HiBench Hadoop and HPC benchmarks to investigate the benefits of deploying Catalina CSDs in the distributed processing environments. The experimental results show up to 2.2× improvement in performance and 4.3× reduction in energy consumption, respectively, for running Hadoop MapReduce benchmarks. Additionally, thanks to the Neon SIMD engines, the performance and energy efficiency of DFT algorithms are improved up to 5.4× and 8.9×, respectively.

High Performance Storage for Big Data Analytics and Visualization

2018 ◽  
pp. 254-275
Author(s):  
Armando Fandango ◽  
William Rivera
Keyword(s):  
Big Data ◽  
High Speed ◽  
High Performance ◽  
File System ◽  
Predictive Analytics ◽  
Big Data Analytics ◽  
File Systems ◽  
Distributed Applications ◽  
System Level ◽  
File Formats

Scientific Big Data being gathered at exascale needs to be stored, retrieved and manipulated. The storage stack for scientific Big Data includes a file system at the system level for physical organization of the data, and a file format and input/output (I/O) system at the application level for logical organization of the data; both of them of high-performance variety for exascale. The high-performance file system is designed with concurrent access, high-speed transmission and fault tolerance characteristics. High-performance file formats and I/O are designed to allow parallel and distributed applications with easy and fast access to Big Data. These specialized file formats make it easier to store and access Big Data for scientific visualization and predictive analytics. This chapter provides a brief review of the characteristics of high-performance file systems such as Lustre and GPFS, and high-performance file formats such as HDF5, NetCDF, MPI-IO, and HDFS.

A microdialysis-based analytical system for dynamic monitoring of arsenic transformation under microbial activity

The Analyst ◽  
2017 ◽  
Vol 142 (24) ◽  
pp. 4737-4743
Author(s):  
Keng-Chang Hsu ◽  
Jing-Ru Hsieh ◽  
Ya-Ching Chen ◽  
Pi-Fu Hsu ◽  
Chih-Chang Hung ◽  
...  
Keyword(s):  
Inductively Coupled Plasma ◽  
High Performance ◽  
Arsenic Species ◽  
Culture Broth ◽  
Dynamic Monitoring ◽  
Inductively Coupled ◽  
Icp Ms ◽  
Plasma Mass Spectrometry ◽  
Arsenic Transformation ◽  
Analytical System

In this study, a microdialysis (MD) technique was combined with high-performance liquid chromatography/inductively coupled plasma mass spectrometry (HPLC-ICP-MS) for continuous monitoring of the dynamic variations of arsenic species in a microbe-inoculated culture broth.

Internet-Oriented Environment for Scientific Computing Resource Sharing

2012 ◽  
Vol 241-244 ◽  
pp. 2953-2956
Author(s):  
Shu Fang Zhang ◽  
Jun Han ◽  
Fei Jiang
Keyword(s):  
Resource Sharing ◽  
High Performance ◽  
Scientific Computing ◽  
Distributed Applications ◽  
Computing Environment ◽  
Resource Monitoring ◽  
Computing Resource ◽  
System Resource ◽  
Measurement Scheduling ◽  
Application Execution

In this paper, we introduced a scientific computing environment for Internet-Oriented computing resource sharing, abbreviate ISCEs, which is a high-performance computing environment that allows users to write and evaluate parallel distributed applications for different hardware and software configurations using a web interface. We described the software architecture of ISCEs by emphasizing Application editor, Application Scheduling Components, and Application execution/runtime modules. ISCEs is efficient which is strongly supported by the time measurement scheduling polices. The system resource monitoring can also benefit a lot from the Application execution/runtime modules. The results obtained from performance analysis show that Scalability and Speedup of ISCEs was good.

scholarly journals Massively multi-user online platform for large-scale applications

2021 ◽  
Author(s):  
Allen Yen-Cheng Yu
Keyword(s):  
Grid Computing ◽  
High Performance ◽  
Large Scale ◽  
Distributed Applications ◽  
Service Architecture ◽  
Online Application ◽  
Online Platform ◽  
Massively Multiplayer Online Game ◽  
And Performance

Many large-scale online applications enable thousands of users to access their services simultaneously. However, the overall service quality of an online application usually degrades when the number of users increases because, traditionally, centralized server architecture does not scale well. In order to provide better Quality of Service (QoS), service architecture such as Grid computing can be used. This type of architecture offers service scalability by utilizing heterogeneous hardware resources. In this thesis, a novel design of Grid computing middleware, Massively Multi-user Online Platform (MMOP), which integrates the Peer-to-Peer (P2P) structured overlays, is proposed. The objectives of this proposed design are to offer scalability and system design flexibility, simplify development processes of distributed applications, and improve QoS by following specified policy rules. A Massively Multiplayer Online Game (MMOG) has been created to validate the functionality and performance of MMOP. The simulation results have demonstrated that MMOP is a high performance and scalable servicing and computing middleware.

scholarly journals Massively multi-user online platform for large-scale applications

2021 ◽  
Author(s):  
Allen Yen-Cheng Yu
Keyword(s):  
Grid Computing ◽  
High Performance ◽  
Large Scale ◽  
Distributed Applications ◽  
Service Architecture ◽  
Online Application ◽  
Online Platform ◽  
Massively Multiplayer Online Game ◽  
And Performance

Many large-scale online applications enable thousands of users to access their services simultaneously. However, the overall service quality of an online application usually degrades when the number of users increases because, traditionally, centralized server architecture does not scale well. In order to provide better Quality of Service (QoS), service architecture such as Grid computing can be used. This type of architecture offers service scalability by utilizing heterogeneous hardware resources. In this thesis, a novel design of Grid computing middleware, Massively Multi-user Online Platform (MMOP), which integrates the Peer-to-Peer (P2P) structured overlays, is proposed. The objectives of this proposed design are to offer scalability and system design flexibility, simplify development processes of distributed applications, and improve QoS by following specified policy rules. A Massively Multiplayer Online Game (MMOG) has been created to validate the functionality and performance of MMOP. The simulation results have demonstrated that MMOP is a high performance and scalable servicing and computing middleware.

scholarly journals Performance Analysis and Evaluation of Hybrid Network using different Integrated Routing Protocols

2013 ◽  
Vol 11 (10) ◽  
pp. 3090-3100 ◽  
Author(s):  
Mr. Rajneesh Narula ◽  
Mr. Kaushal Gandhi
Keyword(s):  
Routing Protocol ◽  
Routing Protocols ◽  
High Performance ◽  
High Capacity ◽  
Network Routing ◽  
Distributed Applications ◽  
Routing Algorithms ◽  
Full Duplex ◽  
Hybrid Network ◽  
Multiple Networks

The increasing demand of computer communication networks are growing rapidly day by day. With the growing need to distribute applications across multiple networks and the availability of high capacity, high-performance intermediate switching nodes, and networks, an efficient routing mechanism has become the core requirement. This research primarily focuses on the design and performance of Hybrid Network incorporating different intra-domain routing algorithms. The performance evaluation of different routing algorithms for the transmission of video- and voice-data streams over Hybrid network is demonstrated in this work.. This allows multiple Ethernet point-to-point links to be bundled into one logical full-duplex channel for Fast Ethernet (10BaseT, 100BaseT, or 1000BaseX). These applications require some QoS support such as guaranteed bandwidth, less delay, less jittering effect and low error rate. The QoS relies on a number of factors along with a suite of robust routing protocols that help to accomplish the task of moving datagram from source to destination with high bandwidth and low delay rate. An effective intra-domain network routing protocol may make distributed applications more efficient across multiple networks with the availability of high capacity and high-performance. A variety of intra-domain routing protocols such as Routing Information Protocol (RIP) and Open Shortest First Protocol (OSPF), Interior Gateway Protocol (IGRP) and Enhanced Interior Gateway Protocol (EIGRP) are available and widely used in designing such high capacity and high performance networks with optimum QoS. We evaluate the performance of these intra-domain routing protocols with IS-IS to recommend the optimum routing protocol to use to provide optimum QoS by means of OPNET Simulator TM. In this thesis work, the following objectives are considered and demonstrated.

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