956 research outputs found
Effects of Communication Protocol Stack Offload on Parallel Performance in Clusters
The primary research objective of this dissertation is to demonstrate that the effects of communication protocol stack offload (CPSO) on application execution time can be attributed to the following two complementary sources. First, the application-specific computation may be executed concurrently with the asynchronous communication performed by the communication protocol stack offload engine. Second, the protocol stack processing can be accelerated or decelerated by the offload engine. These two types of performance effects can be quantified with the use of the degree of overlapping Do and degree of acceleration Daccs. The composite communication speedup metrics S_comm(Do, Daccs) can be used in order to quantify the combined effects of the protocol stack offload. This dissertation thesis is validated empirically. The degree of overlapping Do, the degree of acceleration Daccs, and the communication speedup Scomm characteristic of the system configurations under test are derived in the course of experiments performed for the system configurations of interest. It is shown that the proposed metrics adequately describe the effects of the protocol stack offload on the application execution time. Additionally, a set of analytical models of the networking subsystem of a PC-based cluster node is developed. As a result of the modeling, the metrics Do, Daccs, and Scomm are obtained. The models are evaluated as to their complexity and precision by comparing the modeling results with the measured values of Do, Daccs, and Scomm. The primary contributions of this dissertation research are as follows. First, the metric Daccs and Scomm are introduced in order to complement the Do metric in its use for evaluation of the effects of optimizations in the networking subsystem on parallel performance in clusters. The metrics are shown to adequately describe CPSO performance effects. Second, a method for assessing performance effects of CPSO scenarios on application performance is developed and presented. Third, a set of analytical models of cluster node networking subsystems with CPSO capability is developed and characterised as to their complexity and precision of the prediction of the Do and Daccs metrics
Client-based and Cross-layer Optimized Flow Mobility for Android Devices in Heterogeneous Femtocell/Wi-Fi Networks*
AbstractThe number of subscribers accessing Internet resources from mobile and wireless devices has been increasing continually since i-mode, the first mobile Internet service launched in 1999. The handling and support of dramatic growth of mobile data traffic create serious challenges for the network operators. Due to the spreading of WLAN networks and the proliferation of multi-access devices, offloading from 3G to Wi-Fi seems to be a promising step towards the solution. To solve the bandwidth limitation and coverage issues in 3G/4G environments, femtocells became key players. These facts motivate the design and development of femtocell/Wi-Fi offloading schemes. Aiming to support advanced offloading in heterogeneous networks, in this paper we propose a client-based, cross-layer optimized flow mobility architecture for Android devices in femtocell/Wi-Fi access environments. The paper presents the design, implementation and evaluation details of the aforementioned mechanisms
ACCL+: an FPGA-Based Collective Engine for Distributed Applications
FPGAs are increasingly prevalent in cloud deployments, serving as Smart NICs
or network-attached accelerators. Despite their potential, developing
distributed FPGA-accelerated applications remains cumbersome due to the lack of
appropriate infrastructure and communication abstractions. To facilitate the
development of distributed applications with FPGAs, in this paper we propose
ACCL+, an open-source versatile FPGA-based collective communication library.
Portable across different platforms and supporting UDP, TCP, as well as RDMA,
ACCL+ empowers FPGA applications to initiate direct FPGA-to-FPGA collective
communication. Additionally, it can serve as a collective offload engine for
CPU applications, freeing the CPU from networking tasks. It is user-extensible,
allowing new collectives to be implemented and deployed without having to
re-synthesize the FPGA circuit. We evaluated ACCL+ on an FPGA cluster with 100
Gb/s networking, comparing its performance against software MPI over RDMA. The
results demonstrate ACCL+'s significant advantages for FPGA-based distributed
applications and highly competitive performance for CPU applications. We
showcase ACCL+'s dual role with two use cases: seamlessly integrating as a
collective offload engine to distribute CPU-based vector-matrix multiplication,
and serving as a crucial and efficient component in designing fully FPGA-based
distributed deep-learning recommendation inference
Managing a Fleet of Autonomous Mobile Robots (AMR) using Cloud Robotics Platform
In this paper, we provide details of implementing a system for managing a
fleet of autonomous mobile robots (AMR) operating in a factory or a warehouse
premise. While the robots are themselves autonomous in its motion and obstacle
avoidance capability, the target destination for each robot is provided by a
global planner. The global planner and the ground vehicles (robots) constitute
a multi agent system (MAS) which communicate with each other over a wireless
network. Three different approaches are explored for implementation. The first
two approaches make use of the distributed computing based Networked Robotics
architecture and communication framework of Robot Operating System (ROS) itself
while the third approach uses Rapyuta Cloud Robotics framework for this
implementation. The comparative performance of these approaches are analyzed
through simulation as well as real world experiment with actual robots. These
analyses provide an in-depth understanding of the inner working of the Cloud
Robotics Platform in contrast to the usual ROS framework. The insight gained
through this exercise will be valuable for students as well as practicing
engineers interested in implementing similar systems else where. In the
process, we also identify few critical limitations of the current Rapyuta
platform and provide suggestions to overcome them.Comment: 14 pages, 15 figures, journal pape
On the Exploration of FPGAs and High-Level Synthesis Capabilities on Multi-Gigabit-per-Second Networks
Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Escuela Politécnica Superior, Departamento de Tecnología Electrónica y de las Comunicaciones. Fecha de lectura: 24-01-2020Traffic on computer networks has faced an exponential grown in recent years.
Both links and communication equipment had to adapt in order to provide
a minimum quality of service required for current needs. However, in recent
years, a few factors have prevented commercial off-the-shelf hardware from
being able to keep pace with this growth rate, consequently, some software tools are
struggling to fulfill their tasks, especially at speeds higher than 10 Gbit/s. For this reason,
Field Programmable Gate Arrays (FPGAs) have arisen as an alternative to address the
most demanding tasks without the need to design an application specific integrated
circuit, this is in part to their flexibility and programmability in the field. Needless to say,
developing for FPGAs is well-known to be complex. Therefore, in this thesis we tackle
the use of FPGAs and High-Level Synthesis (HLS) languages in the context of computer
networks. We focus on the use of FPGA both in computer network monitoring application
and reliable data transmission at very high-speed. On the other hand, we intend to shed
light on the use of high level synthesis languages and boost FPGA applicability in the
context of computer networks so as to reduce development time and design complexity.
In the first part of the thesis, devoted to computer network monitoring. We take advantage
of the FPGA determinism in order to implement active monitoring probes, which
consist on sending a train of packets which is later used to obtain network parameters.
In this case, the determinism is key to reduce the uncertainty of the measurements.
The results of our experiments show that the FPGA implementations are much more
accurate and more precise than the software counterpart. At the same time, the FPGA
implementation is scalable in terms of network speed — 1, 10 and 100 Gbit/s. In the context of passive monitoring, we leverage the FPGA architecture to implement algorithms
able to thin cyphered traffic as well as removing duplicate packets. These two algorithms
straightforward in principle, but very useful to help traditional network analysis tools to
cope with their task at higher network speeds. On one hand, processing cyphered traffic
bring little benefits, on the other hand, processing duplicate traffic impacts negatively in
the performance of the software tools.
In the second part of the thesis, devoted to the TCP/IP stack. We explore the current
limitations of reliable data transmission using standard software at very high-speed.
Nowadays, the network is becoming an important bottleneck to fulfill current needs, in
particular in data centers. What is more, in recent years the deployment of 100 Gbit/s
network links has started. Consequently, there has been an increase scrutiny of how
networking functionality is deployed, furthermore, a wide range of approaches are
currently being explored to increase the efficiency of networks and tailor its functionality
to the actual needs of the application at hand. FPGAs arise as the perfect alternative to
deal with this problem. For this reason, in this thesis we develop Limago an FPGA-based
open-source implementation of a TCP/IP stack operating at 100 Gbit/s for Xilinx’s FPGAs.
Limago not only provides an unprecedented throughput, but also, provides a tiny latency
when compared to the software implementations, at least fifteen times. Limago is a key
contribution in some of the hottest topic at the moment, for instance, network-attached
FPGA and in-network data processing
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Internet Infrastructures for Large Scale Emulation with Efficient HW/SW Co-design
Connected systems are becoming more ingrained in our daily lives with the advent of cloud computing, the Internet of Things (IoT), and artificial intelligence. As technology progresses, we expect the number of networked systems to rise along with their complexity. As these systems become abstruse, it becomes paramount to understand their interactions and nuances. In particular, Mobile Ad hoc Networks (MANET) and swarm communication systems exhibit added complexity due to a multitude of environmental and physical conditions. Testing these types of systems is challenging and incurs high engineering and deployment costs. In this work, we propose a scalable MANET emulation framework using virtualized internet infrastructures that generalizes an assortment of application spaces with diverse attributes. We then quantify the architecture using various evaluation techniques to determine both feasibility and scalability. Finally, we developed a hardware offload engine for virtualized network systems that builds upon recent work in the field
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