Packet and message coalescing techniques can improve energy efficiency. Packet coalescing groups packets into bursts before transmission to reduce overhead from transitioning network links like Ethernet interfaces between active and sleep modes. Message coalescing does a similar grouping at the message level. Evaluating coalescing for Energy Efficient Ethernet, smaller buffers had lower energy usage but increased delay, while larger buffers improved energy savings with higher delay. Message coalescing was also studied for InfiniBand clusters to reduce memory usage.
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is an open access international journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Advance in the WIRELESS SENSOR NETWORK (WISENET) technology is energy efficient routing protocols that promises a wide range of potential applications in both civilian and military areas. In the WISNET the sensor node have a limited transmission range and their processing and storage capabilities as well as their energy sources are limited. So the Equalized Cluster Head Election Routing Protocol (ECHERP) and PEGASIS with Double Cluster Head (PDCH) pursues energy conservation through balanced clustering for Energy Efficiency. In WSN, energy efficient routing protocol is important to increase the network lifetime. ECHERP and PDCH both protocol claims to be energy efficient.
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is an open access international journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Advance in the WIRELESS SENSOR NETWORK (WISENET) technology is energy efficient routing protocols that promises a wide range of potential applications in both civilian and military areas. In the WISNET the sensor node have a limited transmission range and their processing and storage capabilities as well as their energy sources are limited. So the Equalized Cluster Head Election Routing Protocol (ECHERP) and PEGASIS with Double Cluster Head (PDCH) pursues energy conservation through balanced clustering for Energy Efficiency. In WSN, energy efficient routing protocol is important to increase the network lifetime. ECHERP and PDCH both protocol claims to be energy efficient.
Optimal Transmit Power and Packet Size in Wireless Sensor Networks in Shadowe...IDES Editor
This paper investigates the effects of
shadowing on the optimal transmit power required to
sustain the network connectivity while maintaining a
predefined maximum tolerable Bit Error Rate (BER) in
a Wireless Sensor Networks (WSN). Optimization of
transmit power is of great importance in WSN since
sensor nodes are battery driven and optimization helps
to increase battery life by reducing inter node
interference significantly. An infinite Automatic Repeat
Request (ARQ) model has been considered to assess the
impact of shadowing and other network conditions on
energy requirement for successful packet transmission in
WSN. We also find the optimal packet length based on
energy efficiency. Effects of shadowing on optimal packet
size and energy efficiency in packetized data
transmission are also investigated. Further energy
consumption is minimized considering a variable packet
length based transmission. Use of optimal packet size
shows a significant reduction in energy spending.
Bessel Companding Transform for reducing PAPR, OBI and BER in OFDM SystemsIOSR Journals
Abstract : Orthogonal Frequency division multiplexing (OFDM) is a very popular technique in wireless communications which provides excellent robustness to channel fading and immune to interference. OFDM is one of a popular modulation technique for transmitting large amounts of digital data over radio carriers. One of the major problems that had been observed in this is the Peak-To Average power Ratio (PAPR). PAPR is a distortion that had occurred due to large number of sub carriers that are used in OFDM for modulating the digital data. Many techniques were available to reduce the PAPR in OFDM systems, among them the companding technique can be used to enhance the OFDM transmission performance by decreasing the PAPR effectively and hence BER. Here we proposed “Bessel Companding Algorithm” to reduce this significant drawback in OFDM Systems. Keywords : Orthogonal Frequency Division Multiplexing (OFDM), peak to average power ratio (PAPR), bit error rate (BER), Out Band Interference (OBI), Additive White Gaussian Noise (AWGN), Bessel Companding Algorithm, Quadrature Amplitude Modulation (QAM) and Multi Carrier Modulation (MCM).
Virtual backbone trees for most minimalIJCNCJournal
Virtual backbone trees have been used for efficient communication between sink node and any other node
in the deployed area. But all the proposed virtual backbone trees are not fully energy efficient and EVBTs
have few flaws associated with them. In this paper two such virtual backbones are proposed. The motive
behind the first algorithm, Most Minimal Energy Virtual Backbone Tree (MMEVBT), is to minimise the
energy consumption when packets are transmitted between sink and a target sensor node. The energy
consumption is most minimal and optimal and it is shown why it always has minimal energy consumption
during any transfer of packet between every node with the sink node. For every node, route path with most
minimal energy consumption is identified and a new tree node is elected only when a better minimal energy
consumption route is identified for a node to communicate with the sink and vice versa. By moving sink
periodically it is ensured the battery of the nodes near sink is not completely drained out. Another
backbone construction algorithm is proposed which maximises the network lifetime by increasing the
lifetime of all tree nodes. Simulations are done in NS2 to practically test the algorithms and the results are
discussed in detail.
Paper review: "HyperNetworks" by David Ha, Andrew Dai, Quoc V. Le (ICLR2017)
Presented at Tensorflow-KR paper review forum (#PR12) by Taesu Kim
Paper link: https://arxiv.org/abs/1609.09106
Video link: https://www.youtube.com/watch?v=-tUQXSdEsMk (in Korean)
http://www.neosapience.com
(Paper) P2P VIDEO BROADCAST BASED ON PER-PEER TRANSCODING AND ITS EVALUATION ...Naoki Shibata
Shibata, N., Yasumoto, K., and Mori, M.: P2P Video Broadcast based on Per-Peer Transcoding and its Evaluation on PlanetLab, Proc. of 19th IASTED Int'l. Conf. on Parallel and Distributed Computing and Systems (PDCS2007), pp. 478-483, (November 2007).
http://ito-lab.naist.jp/themes/pdffiles/071121.shibata.pdcs2007.pdf
We have previously proposed a P2P video broadcast method called MTcast for simultaneously delivering video to user peers with different quality requirements. In this paper, we design and implement a prototype system of MTcast and report the results of its performance evaluation in the real Internet environment. MTcast relies on each peer to transcode and forward video to other peers. We conducted experiments on 20 PlanetLab nodes, evaluated startup delay and recovery time from peer leaving/failure, and confirmed that MTcast achieves practical performance in a real environment.
Performance Comparison of Rerouting Schemes of Multi Protocol Label Switching...IDES Editor
In this paper, we attempt to present a comparison
through rigorous studies (existing conventional models)
following software based modeling and verifications through
simulations in terms of various traffic parameters such as
packet loss, Recovery Time (Latency), reordering of packets
including recovery time for various widely used path recovery
models for the purpose of end-to-end recovery of LSPs in
MPLS domains using NS2 simulator.
In this we discuss about DATA RATE LIMITS
Two theoretical formulas were developed to calculate the data rate:
Nyquist bit rate for a noiseless channel
BitRate = 2 * bandwidth * log 2 L
2: Shannon Capacity for a noisy channel
Capacity = bandwidth * log 2 (1 + SNR)
...............
PERFORMANCE (Network PERFORMANCE) :
Bandwidth: ( Bandwidth in Hertz and Bandwidth in Bits per Seconds) :
Throughput:
These above topics covered in this slide
Thanks You!
TSSB Brain Initiative - Overview of Nano and Molecular Communications and Bra...Walton Institute
This was a presentation given by Dr. Sasitharan Balasubramaniam, Director of Research at TSSG, in which he presented his current research in developing miniature devices for Brain implants. The talk focused on two types of implants, which includes (i) nanoelectronics that are used to stimulate neutrons, (ii) engineered cells that transfect and communicate to neurons. The talk will also touch on the potential applications for these types of devices.
Clustering Based Lifetime Maximizing Aggregation Tree for Wireless Sensor Net...IJASCSE
Energy efficiency is the most important issue in all facets of wireless sensor networks (WSNs) operations because of the limited and non-replenish able energy supply. The data aggregation mechanism is one of the possible solutions to prolong the lifetime of sensor nodes and on the other hand it also helps in eliminating the data redundancy and improving the accuracy of information gathering, is essential for WSNs. In this paper we propose a Clustering based lifetime maximizing aggregation tree (CLMAT) in which we create aggregation tree which aim to reduce energy consumption.
Optimal Transmit Power and Packet Size in Wireless Sensor Networks in Shadowe...IDES Editor
This paper investigates the effects of
shadowing on the optimal transmit power required to
sustain the network connectivity while maintaining a
predefined maximum tolerable Bit Error Rate (BER) in
a Wireless Sensor Networks (WSN). Optimization of
transmit power is of great importance in WSN since
sensor nodes are battery driven and optimization helps
to increase battery life by reducing inter node
interference significantly. An infinite Automatic Repeat
Request (ARQ) model has been considered to assess the
impact of shadowing and other network conditions on
energy requirement for successful packet transmission in
WSN. We also find the optimal packet length based on
energy efficiency. Effects of shadowing on optimal packet
size and energy efficiency in packetized data
transmission are also investigated. Further energy
consumption is minimized considering a variable packet
length based transmission. Use of optimal packet size
shows a significant reduction in energy spending.
Bessel Companding Transform for reducing PAPR, OBI and BER in OFDM SystemsIOSR Journals
Abstract : Orthogonal Frequency division multiplexing (OFDM) is a very popular technique in wireless communications which provides excellent robustness to channel fading and immune to interference. OFDM is one of a popular modulation technique for transmitting large amounts of digital data over radio carriers. One of the major problems that had been observed in this is the Peak-To Average power Ratio (PAPR). PAPR is a distortion that had occurred due to large number of sub carriers that are used in OFDM for modulating the digital data. Many techniques were available to reduce the PAPR in OFDM systems, among them the companding technique can be used to enhance the OFDM transmission performance by decreasing the PAPR effectively and hence BER. Here we proposed “Bessel Companding Algorithm” to reduce this significant drawback in OFDM Systems. Keywords : Orthogonal Frequency Division Multiplexing (OFDM), peak to average power ratio (PAPR), bit error rate (BER), Out Band Interference (OBI), Additive White Gaussian Noise (AWGN), Bessel Companding Algorithm, Quadrature Amplitude Modulation (QAM) and Multi Carrier Modulation (MCM).
Virtual backbone trees for most minimalIJCNCJournal
Virtual backbone trees have been used for efficient communication between sink node and any other node
in the deployed area. But all the proposed virtual backbone trees are not fully energy efficient and EVBTs
have few flaws associated with them. In this paper two such virtual backbones are proposed. The motive
behind the first algorithm, Most Minimal Energy Virtual Backbone Tree (MMEVBT), is to minimise the
energy consumption when packets are transmitted between sink and a target sensor node. The energy
consumption is most minimal and optimal and it is shown why it always has minimal energy consumption
during any transfer of packet between every node with the sink node. For every node, route path with most
minimal energy consumption is identified and a new tree node is elected only when a better minimal energy
consumption route is identified for a node to communicate with the sink and vice versa. By moving sink
periodically it is ensured the battery of the nodes near sink is not completely drained out. Another
backbone construction algorithm is proposed which maximises the network lifetime by increasing the
lifetime of all tree nodes. Simulations are done in NS2 to practically test the algorithms and the results are
discussed in detail.
Paper review: "HyperNetworks" by David Ha, Andrew Dai, Quoc V. Le (ICLR2017)
Presented at Tensorflow-KR paper review forum (#PR12) by Taesu Kim
Paper link: https://arxiv.org/abs/1609.09106
Video link: https://www.youtube.com/watch?v=-tUQXSdEsMk (in Korean)
http://www.neosapience.com
(Paper) P2P VIDEO BROADCAST BASED ON PER-PEER TRANSCODING AND ITS EVALUATION ...Naoki Shibata
Shibata, N., Yasumoto, K., and Mori, M.: P2P Video Broadcast based on Per-Peer Transcoding and its Evaluation on PlanetLab, Proc. of 19th IASTED Int'l. Conf. on Parallel and Distributed Computing and Systems (PDCS2007), pp. 478-483, (November 2007).
http://ito-lab.naist.jp/themes/pdffiles/071121.shibata.pdcs2007.pdf
We have previously proposed a P2P video broadcast method called MTcast for simultaneously delivering video to user peers with different quality requirements. In this paper, we design and implement a prototype system of MTcast and report the results of its performance evaluation in the real Internet environment. MTcast relies on each peer to transcode and forward video to other peers. We conducted experiments on 20 PlanetLab nodes, evaluated startup delay and recovery time from peer leaving/failure, and confirmed that MTcast achieves practical performance in a real environment.
Performance Comparison of Rerouting Schemes of Multi Protocol Label Switching...IDES Editor
In this paper, we attempt to present a comparison
through rigorous studies (existing conventional models)
following software based modeling and verifications through
simulations in terms of various traffic parameters such as
packet loss, Recovery Time (Latency), reordering of packets
including recovery time for various widely used path recovery
models for the purpose of end-to-end recovery of LSPs in
MPLS domains using NS2 simulator.
In this we discuss about DATA RATE LIMITS
Two theoretical formulas were developed to calculate the data rate:
Nyquist bit rate for a noiseless channel
BitRate = 2 * bandwidth * log 2 L
2: Shannon Capacity for a noisy channel
Capacity = bandwidth * log 2 (1 + SNR)
...............
PERFORMANCE (Network PERFORMANCE) :
Bandwidth: ( Bandwidth in Hertz and Bandwidth in Bits per Seconds) :
Throughput:
These above topics covered in this slide
Thanks You!
TSSB Brain Initiative - Overview of Nano and Molecular Communications and Bra...Walton Institute
This was a presentation given by Dr. Sasitharan Balasubramaniam, Director of Research at TSSG, in which he presented his current research in developing miniature devices for Brain implants. The talk focused on two types of implants, which includes (i) nanoelectronics that are used to stimulate neutrons, (ii) engineered cells that transfect and communicate to neurons. The talk will also touch on the potential applications for these types of devices.
Clustering Based Lifetime Maximizing Aggregation Tree for Wireless Sensor Net...IJASCSE
Energy efficiency is the most important issue in all facets of wireless sensor networks (WSNs) operations because of the limited and non-replenish able energy supply. The data aggregation mechanism is one of the possible solutions to prolong the lifetime of sensor nodes and on the other hand it also helps in eliminating the data redundancy and improving the accuracy of information gathering, is essential for WSNs. In this paper we propose a Clustering based lifetime maximizing aggregation tree (CLMAT) in which we create aggregation tree which aim to reduce energy consumption.
Delay Constrained Energy Efficient Data Transmission over WSNpaperpublications3
Abstract: In wireless sensor network generally concentrate on minimization of energy Consumption, Also reducing energy saving and end to end delay. Reduced the end to end delay is one of the main challenges in the Wireless Sensor Networks. In TDMA providing reliable packet transmission and two transmission scheduling schemes are used to maximize the end-end reliability within a delay bound in packet transmission called dedicated scheduling and shared scheduling. In addition, they formulate solutions for implementing two algorithms into two basic routing algorithms, single-path routing and any-path routing algorithm. The proposed system presented energy efficient sleep scheduling algorithm for reducing the energy for delay constrained in WLAN. This algorithm to maximize the energy saving for packet delay constraints and it determines sleep period and wake up time to be minimized, the aim of this project is proposed to maximize the length of sleep time under packet deadline constraints using green call algorithm. Keywords: Delay-constrained applications, energy efficiency, Sleep scheduling, wireless sensor network.
Title: Delay Constrained Energy Efficient Data Transmission over WSN
Author: H. Hasina Begaum
ISSN 2350-1022
International Journal of Recent Research in Mathematics Computer Science and Information Technology
Paper Publications
Packet losses at IP network are common behavior at
the time of congestion. The TCP traffic is explained as in
terms of load and capacity. The load should be measured as
number of sender actively competes for a bottleneck link and
the capacity as the total network buffering available to those
senders. Though there are many congestion mechanism
already in practice like congestion window, slow start,
congestion avoidance, fast transmit but still we see erratic
behavior when there is a large traffic. The TCP protocol that
controls sources send rates degrades rapidly if the network
cannot store at least a few packets per active connection. Thus
the amount of router buffer space required for good
performance scales with the number of active connections
and the bandwidth utilization by each active connections. As
in the current practice, the buffer space does not scale in this
way and router drops the packet without looking at bandwidth
utilization of each connections. The result is global
synchronization and phase effect as well as packet from the
unlucky sender will be frequently dropped. The simultaneous
requirements of low queuing delay and of large buffer
memories for large numbers of connections pose a problem.
Routers should enforce a dropping policy by proportional to
the bandwidth utilization by each active connection. Router
will provision the buffering mechanism when processing slows
down. This study explains the existing problem with drop-tail
and RED routers and proposes the new mechanism to predict
the effective bandwidth utilization of the clients depending
on their history of utilization and drop the packet in different
pattern after analyzing the network bandwidth utilization at
each specific interval of time
ENHANCEMENT OF TCP FAIRNESS IN IEEE 802.11 NETWORKScscpconf
The usage of fixed buffers in 802.11 networks has a number of disadvantages associated with
it. This includes high delay, reduced throughput and inefficient channel utilisation. To
overcome this, a dynamic buffer sizing algorithm, the A* algorithm has been implemented at
the access point. In this algorithm buffer size is dynamically adjusted depending upon the
current channel conditions and hence delay is reduced and the throughput is maintained. But
in 802.11 networks with DCF collision avoidance mechanism, it creates significant amount of
unfairness between the upstream and downstream TCP flows, with clusters of upstream ACKs
blocking downstream data at the access point. Thus a variation of the Explicit Window
Adaptation (EWA) scheme has been used to regulate the queuing time of the upload clients by
calculating the feedback value at the access point. This creates fairness and increases the number of transmission opportunities for the downstream traffic
LEACH is a hierarchical protocol in which most nodes transmit to cluster heads, and the cluster heads aggregate and compress the data and forward it to the base station (sink).In LEACH, a TDMA-based MAC protocol is integrated with clustering and a simple “routing” protocol. The goal of LEACH is to lower the energy consumption required to create and maintain clusters or to use the energy of the nodes in such a manner so as to improve the life time of a wireless sensor network. In this paper we are presenting an overview of the different protocol changes made in LEACH to improve network lifetime, throughput, coverage area of network etc.
LEACH is a hierarchical protocol in which most nodes transmit to cluster heads, and the cluster heads aggregate and
compress the data and forward it to the base station (sink).In LEACH, a TDMA-based MAC protocol is integrated with clustering and
a simple “routing” protocol. The goal of LEACH is to lower the energy consumption required to create and maintain clusters or to use
the energy of the nodes in such a manner so as to improve the life time of a wireless sensor network. In this paper we are presenting an
overview of the different protocol changes made in LEACH to improve network lifetime, throughput, coverage area of network etc.
Communication Performance Over A Gigabit Ethernet NetworkIJERA Editor
A present computing imposes heavy demands on the optical communication network. Gigabit Ethernet technology can provide the required bandwidth to meet these demands. However, it has also involve the communication Impediment to progress from network media to TCP(Transfer control protocol) processing. In this paper, present an overview of Gigabit per second Ethernet technology and study the end-to-end Gigabit Ethernet communication bandwidth and retrieval time. Performance graphs are collected using NetPipe in this clearly show the performance characteristics of TCP/IP over Gigabit Ethernet. These indicate the impact of a number of factors such as processor speeds, network adaptors, versions of the Linux Kernel or opnet softwar and device drivers, and TCP/IP(Internet protocol) tuning on the performance of Gigabit Ethernet between two Pentium II/350 PCs. Among the important conclusions are the marked superiority of the 2.1.121 and later development kernels and 2.2.x production kernels of Linux or opnet softwar used and that the ability to increase the MTU(maximum transmission unit) Further than the Ethernet standard of 1500 could significantly enhance the throughput reachable.
K dag based lifetime aware data collection in wireless sensor networksijwmn
Wireless Sensor Networks need to be organized for efficient data collection and lifetime maximization. In
this paper, we propose a novel routing structure, namely k-DAG, to balance the load of the base station's
neighbours while providing the worst-case latency guarantee for data collection, and a distributed
algorithm for construction a k-DAG based on a SPD (Shortest Path DAG). In a k-DAG, the lengths of the
longest path and the shortest path of each sensor node to the base station differ by at most k. By adding
sibling edges to a SPD, our distributed algorithm allows critical nodes to have more routing choices. The
simulation results show that our approach significantly outperforms the SPD-based data collection
approach in both network lifetime and load balance.
The maximization of a networks lifetime is an important part of research in the present scenario. In ad hoc network, the topology of network changes frequently due to the mobility of mobile nodes where the communication is possible without any network infrastructure. Mobile nodes have limited energy resources so that the energy efficient routing should be provided which increases the life time of the network. The existing routing mechanisms do not consider energy of nodes for data transmission. In this paper a novel approach is analyzed to improve the networks lifetime where the data transfer is based on the minimum hop count and residual energy of the mobile nodes. The analysis is carried out by using the network simulator and the simulation results shows that the proposed work provides an energy efficient routing in ad hoc networks.
An Improved Energy Efficient Wireless Sensor Networks Through Clustering In C...Editor IJCATR
One of the major reason for performance degradation in Wireless sensor network is the overhead due to control packet and
packet delivery degradation. Clustering in cross layer network operation is an efficient way manage control packet overhead and which
ultimately improve the lifetime of a network. All these overheads are crucial in a scalable networks. But the clustering always suffer
from the cluster head failure which need to be solved effectively in a large network. As the focus is to improve the average lifetime of
sensor network the cluster head is selected based on the battery life of nodes. The cross-layer operation model optimize the overheads
in multiple layer and ultimately the use of clustering will reduce the major overheads identified and their by the energy consumption
and throughput of wireless sensor network is improved. The proposed model operates on two layers of network ie., Network Layer
and Transport Layer and Clustering is applied in the network layer . The simulation result shows that the integration of two layers
reduces the energy consumption and increases the throughput of the wireless sensor networks.
An Improved Energy Efficient Wireless Sensor Networks Through Clustering In C...Editor IJCATR
One of the major reason for performance degradation in Wireless sensor network is the overhead due to control packet and
packet delivery degradation. Clustering in cross layer network operation is an efficient way manage control packet overhead and which
ultimately improve the lifetime of a network. All these overheads are crucial in a scalable networks. But the clustering always suffer
from the cluster head failure which need to be solved effectively in a large network. As the focus is to improve the average lifetime of
sensor network the cluster head is selected based on the battery life of nodes. The cross-layer operation model optimize the overheads
in multiple layer and ultimately the use of clustering will reduce the major overheads identified and their by the energy consumption
and throughput of wireless sensor network is improved. The proposed model operates on two layers of network ie., Network Layer
and Transport Layer and Clustering is applied in the network layer . The simulation result shows that the integration of two layers
reduces the energy consumption and increases the throughput of the wireless sensor networks.
An Improved Energy Efficient Wireless Sensor Networks Through Clustering In C...Editor IJCATR
One of the major reason for performance degradation in Wireless sensor network is the overhead due to control packet and packet delivery degradation. Clustering in cross layer network operation is an efficient way manage control packet overhead and which ultimately improve the lifetime of a network. All these overheads are crucial in a scalable networks. But the clustering always suffer from the cluster head failure which need to be solved effectively in a large network. As the focus is to improve the average lifetime of sensor network the cluster head is selected based on the battery life of nodes. The cross-layer operation model optimize the overheads in multiple layer and ultimately the use of clustering will reduce the major overheads identified and their by the energy consumption and throughput of wireless sensor network is improved. The proposed model operates on two layers of network ie., Network Layer and Transport Layer and Clustering is applied in the network layer . The simulation result shows that the integration of two layers reduces the energy consumption and increases the throughput of the wireless sensor networks.
An Improved Energy Efficient Wireless Sensor Networks Through Clustering In C...Editor IJCATR
One of the major reason for performance degradation in Wireless sensor network is the overhead due to control packet and packet delivery degradation. Clustering in cross layer network operation is an efficient way manage control packet overhead and which ultimately improve the lifetime of a network. All these overheads are crucial in a scalable networks. But the clustering always suffer from the cluster head failure which need to be solved effectively in a large network. As the focus is to improve the average lifetime of sensor network the cluster head is selected based on the battery life of nodes. The cross-layer operation model optimize the overheads in multiple layer and ultimately the use of clustering will reduce the major overheads identified and their by the energy consumption and throughput of wireless sensor network is improved. The proposed model operates on two layers of network ie., Network Layer and Transport Layer and Clustering is applied in the network layer . The simulation result shows that the integration of two layers reduces the energy consumption and increases the throughput of the wireless sensor networks.
Designing for Privacy in Amazon Web ServicesKrzysztofKkol1
Data privacy is one of the most critical issues that businesses face. This presentation shares insights on the principles and best practices for ensuring the resilience and security of your workload.
Drawing on a real-life project from the HR industry, the various challenges will be demonstrated: data protection, self-healing, business continuity, security, and transparency of data processing. This systematized approach allowed to create a secure AWS cloud infrastructure that not only met strict compliance rules but also exceeded the client's expectations.
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...Globus
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
SOCRadar Research Team: Latest Activities of IntelBrokerSOCRadar
The European Union Agency for Law Enforcement Cooperation (Europol) has suffered an alleged data breach after a notorious threat actor claimed to have exfiltrated data from its systems. Infamous data leaker IntelBroker posted on the even more infamous BreachForums hacking forum, saying that Europol suffered a data breach this month.
The alleged breach affected Europol agencies CCSE, EC3, Europol Platform for Experts, Law Enforcement Forum, and SIRIUS. Infiltration of these entities can disrupt ongoing investigations and compromise sensitive intelligence shared among international law enforcement agencies.
However, this is neither the first nor the last activity of IntekBroker. We have compiled for you what happened in the last few days. To track such hacker activities on dark web sources like hacker forums, private Telegram channels, and other hidden platforms where cyber threats often originate, you can check SOCRadar’s Dark Web News.
Stay Informed on Threat Actors’ Activity on the Dark Web with SOCRadar!
Paketo Buildpacks : la meilleure façon de construire des images OCI? DevopsDa...Anthony Dahanne
Les Buildpacks existent depuis plus de 10 ans ! D’abord, ils étaient utilisés pour détecter et construire une application avant de la déployer sur certains PaaS. Ensuite, nous avons pu créer des images Docker (OCI) avec leur dernière génération, les Cloud Native Buildpacks (CNCF en incubation). Sont-ils une bonne alternative au Dockerfile ? Que sont les buildpacks Paketo ? Quelles communautés les soutiennent et comment ?
Venez le découvrir lors de cette session ignite
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
A Comprehensive Look at Generative AI in Retail App Testing.pdfkalichargn70th171
Traditional software testing methods are being challenged in retail, where customer expectations and technological advancements continually shape the landscape. Enter generative AI—a transformative subset of artificial intelligence technologies poised to revolutionize software testing.
Modern design is crucial in today's digital environment, and this is especially true for SharePoint intranets. The design of these digital hubs is critical to user engagement and productivity enhancement. They are the cornerstone of internal collaboration and interaction within enterprises.
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
Into the Box Keynote Day 2: Unveiling amazing updates and announcements for modern CFML developers! Get ready for exciting releases and updates on Ortus tools and products. Stay tuned for cutting-edge innovations designed to boost your productivity.
How Recreation Management Software Can Streamline Your Operations.pptxwottaspaceseo
Recreation management software streamlines operations by automating key tasks such as scheduling, registration, and payment processing, reducing manual workload and errors. It provides centralized management of facilities, classes, and events, ensuring efficient resource allocation and facility usage. The software offers user-friendly online portals for easy access to bookings and program information, enhancing customer experience. Real-time reporting and data analytics deliver insights into attendance and preferences, aiding in strategic decision-making. Additionally, effective communication tools keep participants and staff informed with timely updates. Overall, recreation management software enhances efficiency, improves service delivery, and boosts customer satisfaction.
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2. 『 Packet Coalescing and Server Substitution
for Energy-Proportional Operation of
Network Links and Data Servers 』
Mostowfi, Mehrgan, "Packet Coalescing and Server Substitution for Energy-Proportional Operation of
Network Links and Data Servers" (2013). Graduate School Theses and Dissertations.
http://scholarcommons.usf.edu/etd/4732
3. • PKT / MSG Coalescing 의 구분
• Energy Efficient Ethernet의 Packet Coalescing
• EEE Coalescer 버퍼 크기에 따른 에너지 소비량 비교
5. 메시지 패킷
네트워크를 통해
전송하기 쉽도록 자른
데이터의 전송단위.
통신 수단에 의한 전달에
적합한 언어나 부호로
작성된 단위 정보 또는
전송된 단위 정보.
[네이버 지식백과] 패킷 [packet] (두산백과)
[네이버 지식백과] 메시지 [message] (IT용어사전, 한국정보통신기술협회)
즉, ‘메시지’가 네트워크를 통해 전송 될 때,
‘패킷’이라는 단위로 변환(이를 단편화라 함)된다.
6. packet fragmentation
via ‘Transport
& Network Layer’
Packet
Capacity == 1500
case 1. strlen(msg) > Capacity
case 2. strlen(msg) < Capacity
- TCP
- UDP
- IP
단편화(패킷으로 변환)의 두 가지 경우
7. Case 1.
strlen(msg) > Capacity
Packet
Capacity == 1500
msgmsgmsg
1500 - socketHeader
필요한 크기만큼
메시지를 잘라
패킷으로 변환.
수신측에선
잘게 나누어진
패킷의 순서를
해석한 후
메시지 재 조립
packet fragmentation
via ‘Transport
& Network Layer’
8. Case 2.
strlen(msg) < Capacity
Capacity < 1500
msg
전달된 메시지가
바로 패킷으로 변환.
pkt
packet fragmentation
via ‘Transport
& Network Layer’
9. Case 3.
strlen(msg) < Capacity
&& Too Much Message
msg
pkt
msgmsgmsgmsgmsg
pktpktpktpktpkt
n
n
불필요하게
많은 수의
패킷이 생성.
n 만큼의 변환 과정이 필요.
불필요하게
많은 수의
전송이 실행.
n 만큼의 전송 과정이 필요.
10. n
(ex: n=10,
msg size=1500byte)
Case 3. Solution 1.
PKT Coalescing
msg
pkt
msgmsgmsgmsgmsg
pktpktpktpktpkt
n
(ex: n=10,
msg size=1500byte)
pkt pkt ··· pkt pkt
Packet Coalescing
n
‘패킷’을 네트워크 카드가
보낼 수 있을 만큼
모아서 한꺼번에 전송.
현재 EEE 에서 사용하는 방식.
[NIC 카드]
13. 에너지 효율 이더넷
• 에너지 효율 이더넷(영어: Energy-Efficient Ethernet)은 데이
터를 적게 쓰는 시기에 소비 전력을 낮춤으로써 연선과 백플레인
이더넷 계열의 컴퓨터 네트워킹 표준을 강화하는 기술이다. 50%
이상 소비 전력을 낮추지만 기존의 장비와 완전한 호환성을 유지
하는 것이 목적이다.[1] IEEE는 최종 표준을 2010년 9월에 승인
하였다.[2] 이 표준이 승인되기 전까지는 그린 이더넷(Green
Ethernet)이라는 이름을 사용했다.
[1] Sean Michael Kerner (2009. 7. 17 ). Energy Efficient Ethernet hits standards milestone
— InternetNews:The Blog — Sean Michael Kerner . 《Internetnews blog》
[2] "IEEE ratifies new 8023az standard to reduce network energy footprint ", (2010. 10. 5 )
14. 참고부분 - Chapter 3: Packet Coalescing
for Energy Efficient Ethernet
3.1 An Analytical Energy-Delay Model for a Count-based Packet Coalescer
3.1.1 Energy-Delay Model for Coalescer
3.1.2 Delay Model for Downstream Queue
3.1.3 Numerical Results
3.2 Reducing the Energy Consumption of EEE by Packet Coalescing
3.2.1 Simulation Model of EEE with Packet Coalescing
3.2.2 Experiments
3.2.3 Results
3.2.4 Comparison Between the Analytical Model of Coalescing and the
Simulation Model of EEE with Packet Coalescing
3.3 Extending Savings of Packet Coalescing Beyond Links in Ethernet Switches
3.3.1 Switch Energy Use and Transition Times
3.3.2 The Synchronized Coalescing Method
3.3.2.1 Simple Synchronized Coalescing
3.3.2.2 Adaptive Coalescing
3.3.3 Evaluation by Simulation
3.3.4 Results and Discussion
3.4 Chapter Summary
15. EEE uses a Low Power Idle (LPI) mode to reduce power
consumption between packet transmissions. EEE has
transition times Ts(wake-to-sleep) and Tw(sleep-to-
wake), which are significantly greater than a single
packet transmission time for both 1 and 10 Gb/s EEE.
By coalescing arriving packets into bursts, the overhead
of Ts and Tw can be reduced and nearly energy-
proportional operation can be achieved. The trade-off in
coalescing is increased packet delay at the sender and,
potentially, also in downstream switches or routers.
* EEE : Energy Efficient Ethernet
16. In packet coalescing, a FIFO queue in the Ethernet interface (in the host
NIC and switch or router line card) is used to collect, or coalesce, multiple
packets before sending them on a link as a burst of back-to-back packets.
This FIFO queue is called a coalescer.
Packet coalescing is already used in many high-speed Ethernet interfaces
– mostly on the receive side – to reduce CPU overhead for packet
processing [73]. Packet coalescing can be based on packet count and/or
time from first packet arrival.
In packet coalescing based on packet count (count-based coalescing),
the coalescer collects a certain number of packets before sending them on
the link in a single burst.
In packet coalescing based on time from first packet arrival, the coalescer
sets a timer, called the coalescing timer, to a certain predefined time upon
the arrival of the first packet to an empty coalescer. The timer counts down
to zero. When the timer reaches zero (or expires), the coalescer sends the
packets which are collected in the coalescer on the link.
1
2
Counter에 의한 Coalescing
Timer에 의한 Coalescing
17. FSM of PKT Coalescing
count-based time-based
(simple synchronized coalescing)
18. EEE with Packet Coalescing
CTimer : maintain PKT
Coalescing time.
WTimer : maintain time
spent in ‘Wakeup’.
STimer : maintain time
spent in ‘Sleep’.
21. Ps : Power Consumption in LPI mode
Pa : Power Consumption during Active mode
tLPI : time spent in the LPI mode
tws : Sleep Time (needed to enter the low-power mode)
tsw : Wake-up Time (required to exit the low-power mode)
전력소모공식
* 인용 : 『 Performance Evaluation of Energy Efficient Ethernet 』
P. Reviriego, J. A. Hern´andez, D. Larrabeiti, and J. A. Maestro
IEEE COMMUNICATIONS LETTERS, VOL. 13, NO. 9, SEPTEMBER 2009
22. The factors in these
experiments are :
• The power consumption in the LPI mode, Ps, is
assumed to be 10% according to the estimations made
by different NIC manufacturers during the
standardization process of EEE *
• The power consumption during transitions is also
assumed 100% (Pa) also based on estimations made by
different NIC manufacturers. *
• The power consumption in Active mode is obviously
100% of the link’s consumption. *
* 인용 : 『 Performance Evaluation of Energy Efficient Ethernet 』
P. Reviriego, J. A. Hern´andez, D. Larrabeiti, and J. A. Maestro
IEEE COMMUNICATIONS LETTERS, VOL. 13, NO. 9, SEPTEMBER 2009
23. The factors in these
experiments are :
[5] J. Chou, “Low-power idle based EEE 100Base-TX,”
Mar. 2008, in IEEE 802.3az Task Force presentation.
[6] B. Kohl, “10GBase-T power budget summary,”
Mar. 2007, in IEEE 802.3az Task Force presentation.
24. The factors in these
experiments are :
• Tws and Tsw; set to their minimums,
4.48 and 2.88 μs respectively
• Distribution of packet arrivals and packet size; set to
Poisson distribution with fixed packet size of 1500 B.
• For the small coalescer, 12μs and 10 packets are used
for these factors, respectively.
• For the large coalescer, 120μs and 100 packets are
used.
-> 15 KB
-> 150 KB
28. 『 Reducing Connection Memory
Requirements of MPI for InfiniBand
Clusters: A Message Coalescing Approach 』
Matthew J. Koop(1)(2), Terry Jones(2), Dhabaleswar K. Panda(1)
(1) Network-Based Computing Laboratory Department of Computer Science and Engineering
The Ohio State University
(2) Lawrence Livermore National Laboratory Livermore, CA 94550
*Published in :
Cluster Computing and the Grid, 2007. CCGRID 2007.
Seventh IEEE International Symposium on
http://ieeexplore.ieee.org/xpl/login.jsp?
tp=&arnumber=4215416&url=http%3A%2F%2Fieeexplore.ieee.org
%2Fxpls%2Fabs_all.jsp%3Farnumber%3D4215416
32. Feature InfiniBand PCI-X Fibre Channel
1 Gb & 10Gb
Ethernet
Hypertransport Rapid I/O
Bus/link bandwidth 2.5/10/30 Gbps 8.51Gbps 1/2.1Gbps 1 Gb, 10 Gb
12.8, 25.6, 51.2
Gbps
16/3 Gbps
Bus/link bandwidth (fully
duplexed)
5/20/60 Gbps n/a Gbps 2.1/4.2 Gb 2 Gb, 20 Gb
25.6, 51.2, 102
Gbps
32/64Gbps
Pin count 4/16/484 90 4 4, Fiber 55,103,197 40/76
Maximum signal length km Inches km km Inches Inches
Transport media
PCB, Fiber, copper
cable
PCB only
Copper and fiber
cable
Copper and fiber
cable
PCB only PCB only
Simultaneous peer-to-peer
communication
15 VLs + management
lane
X
Three transaction
flows
Native hwd transport support X
In-band management X
Not native; can
use IP
RDMA support X
Native support for virtual interface X
End-to-end management X X X X
Memory partitioning X X
QoS X X Limited X
Reliable X X X X
Scaleable X X X X X
Maximum packet payload 4 KB
Not packet
based
2 KB
1.5 KB (Jumbo: 9
KB)
64 B 256 B
Notes:
1. The raw bandwidth of an InfiniBand 1X link is 2.5 Gbps (per link). Data bandwidth (due to 8B/10B encoding) is 2.0 Gbps for 1X, 8 Gbps for 4X, and 24
Gbps for 12X; twice that for full duplex or 4/16/48 Gbps.
2. The bandwidth of 2-Gb fibre channel is 2.1 Gbps, but the actual raw bandwidth (due to 8B/10B encoding) is 20% lower or around 1.7 Gbps (twice that
for full duplex).
3. Values are for 8B/16B data paths peak at 1-GHz operation. Speeds of 125, 250, and 500 MHz are supported.
4. The pin count for a 1X link is four pins up to 48 pins for a 12X link.
5. Memory partitioning enables multiple hosts to access storage endpoints in a controlled manner based on a key. Access to a particular endpoint is
controlled by this key, so different hosts can have access to different elements in the network.
* InfiniBand: Thinking Outside the Box Design
http://www.eetimes.com/document.asp?doc_id=1204052
33. Feature InfiniBand PCI-X Fibre Channel
1 Gb & 10Gb
Ethernet
Hypertransport Rapid I/O
Bus/link bandwidth 2.5/10/30 Gbps 8.51Gbps 1/2.1Gbps 1 Gb, 10 Gb
12.8, 25.6, 51.2
Gbps
16/3 Gbps
Bus/link bandwidth (fully
duplexed)
5/20/60 Gbps n/a Gbps 2.1/4.2 Gb 2 Gb, 20 Gb
25.6, 51.2, 102
Gbps
32/64Gbps
Pin count 4/16/484 90 4 4, Fiber 55,103,197 40/76
Maximum signal length km Inches km km Inches Inches
Transport media
PCB, Fiber, copper
cable
PCB only
Copper and fiber
cable
Copper and fiber
cable
PCB only PCB only
Simultaneous peer-to-peer
communication
15 VLs + management
lane
X
Three transaction
flows
Native hwd transport support X
In-band management X
Not native; can
use IP
RDMA support X
Native support for virtual interface X
End-to-end management X X X X
Memory partitioning X X
QoS X X Limited X
Reliable X X X X
Scaleable X X X X X
Maximum packet payload 4 KB
Not packet
based
2 KB
1.5 KB (Jumbo: 9
KB)
64 B 256 B
Notes:
1. The raw bandwidth of an InfiniBand 1X link is 2.5 Gbps (per link). Data bandwidth (due to 8B/10B encoding) is 2.0 Gbps for 1X, 8 Gbps for 4X, and 24
Gbps for 12X; twice that for full duplex or 4/16/48 Gbps.
2. The bandwidth of 2-Gb fibre channel is 2.1 Gbps, but the actual raw bandwidth (due to 8B/10B encoding) is 20% lower or around 1.7 Gbps (twice that
for full duplex).
3. Values are for 8B/16B data paths peak at 1-GHz operation. Speeds of 125, 250, and 500 MHz are supported.
4. The pin count for a 1X link is four pins up to 48 pins for a 12X link.
5. Memory partitioning enables multiple hosts to access storage endpoints in a controlled manner based on a key. Access to a particular endpoint is
controlled by this key, so different hosts can have access to different elements in the network.
* InfiniBand: Thinking Outside the Box Design
http://www.eetimes.com/document.asp?doc_id=1204052
Feature InfiniBand
1 Gb & 10Gb
Ethernet
Hypertransport
Bus/link bandwidth 2.5/10/30 Gbps 1 Gb, 10 Gb 51.2 Gbps
Bus/link bandwidth
(fully duplexed)
5/20/60 Gbps 2 Gb, 20 Gb 102 Gbps
Maximum signal
length
km km inches
Transport media
PCB, Fiber,
copper cable
Copper and
fiber cable
PCB only
34. 인피니밴드는 전통적인 이더넷 아키텍처와 같은 계층적 스위치 방식의 네트워크와는 반대로
스위치 패브릭 방식의 토폴리지를 사용한다. 모든 전송은 채널 어댑터에서 시작하거나 끝이 난다.
각 프로세서는 호스트 채널 어댑터(HCA)를 가지고 있으며 각 주변장치에는 타켓 채널 어댑터
(TCA)가 있다. 이러한 어댑터들은 보안 및 QoS를 위하여 정보를 교환할 수 있다.
* INFINIBAND by Carlo kopp
http://www.csse.monash.edu.au/~carlo/SYSTEMS/Infiniband-Intro-0901.html
* http://ko.wikipedia.org/wiki/인피니밴드
* http://etherealmind.com/what-is-the-definition-of-switch-fabric/
스위치 페브릭은 각 노드들이 직물처럼 옹기종
기 엮여있는 모양새.
점대점 연결이라서 라우팅 알고리즘이 필요 없
다.
35. a host channel adapter
(HCA)
a target channel adapter
(TCA)
Channel Adapters
The HCA provides an interface to a
host CPU and memory subsystem,
such as a web server, and supports all
software verbs defined by the
InfiniBand architecture.
A TCA, on the other hand, provides the
connection to an I/O device from
InfiniBand. This I/O card, which could be
a network interface card (NIC), houses a
subset of features necessary for each
device's specific operations.
* InfiniBand: Thinking Outside the Box Design
http://www.eetimes.com/document.asp?doc_id=1204052
36. * High-Performance Buses and Interconnects
http://www.pcmag.com/article2/0,2817,1154809,00.asp
NIC
msg
send/recv via
InfiniBand
HCA 위치 성질
37. - Ethernet 대신 InfiniBand를 사용함으로써,
• Transport / Network Layer에서 진행되던 패킷화 과정이 간소화.
• 따라서 CPU 사용량과 지연시간이 감소.
Pkt Pkt
msg
(kern)
* Enterprise Distributed Systems and Infiniband
http://www.cisco.com/c/en/us/products/collateral/switches/sfs-7000-
series-infiniband-server-switches/prod_white_paper0900aecd804f90f3.html
38. How it Works?
When using a connection-based model, a pair of hosts that wishes to
communicate must each set up a dedicated Queue Pair (QP) for
communication with that peer. Each QP is linked to a Completion Queue (CQ) for
notification of completion. In this connection-based model, there is additional
memory usage with each additional connection.
39. To send a message a descriptor is posted to the QP. This descriptor contains
information about the message to be sent, including the data address, memory
keys, and message length. To receive a message using channel semantics a
receive descriptor must be posted containing the address and length of the buffer.
Upon posting a descriptor, a send Work Queue Entry (WQE), pronounced “wookie,”
is used to track the progress of the request.
Upon completion of a WQE a Completion Queue Entry (CQE), “cookie,” is placed in
the CQ. This method is used in both channel and memory semantics. CQEs can be
obtained by polling the CQ or through an event-based methods.
When a QP is created, the number of send and receive WQEs must be defined.
The number of WQEs allocated determines the number of outstanding send and
receive operations allowed on a single QP. Using a Shared Receive Queue (SRQ)
allows receive WQEs and buffers to be shared rather than per QP, which allows far
better scalability. Benefits are demonstrated in [17] and we will assume SRQ is
being used. Even using a SRQ, however, send WQEs must be posted per QP. Thus,
the number of send WQEs allocated for a QP determines how many outstanding
send operations are allowed for that connection.
* 2.1 InfiniBand Architecture Overview
How it Works?
40. * INFINIBAND by Carlo kopp
http://www.csse.monash.edu.au/~carlo/SYSTEMS/Infiniband-Intro-0901.html
FIFO Queue
HCA는 Work Queue의
내용을 검색, 해당 메시지
를 주기억 장치에서 읽어내
어 패킷으로 변환한다.
전송이 종료되면 해당
Completion Queue의 내용
에 전송 완료 정보를 기록한다.
전송된 패킷은 목적지 노드에서
다시 메시지로 조립되어 Work
Queue에 저장된다.
하드웨어 상세
45. MSG Coalescing Design
1. alter the send flow operation.
2. use the InfiniBand scatter/gather capabilities
instead of packing into the same buffer.
3. cache the MPI tag matching information for each
message.
46. MSG Coalescing Evaluation
Our experimental testbed is a 575-node InfiniBand Linux cluster at Lawrence Livermore National Laboratory.
Each compute node has four 2.5 GHz Opteron 8216 dual-core processors for a total of 8 cores. Total memory
per node is 16GB. Each node has a Mellanox MT25208 DDR HCA. InfiniBand software support is provided
through the OpenFabrics/Gen2 stack [15]. The Intel v9.0 compiler is used for compilation of the MVA- PICH
library and applications.