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Automating Topology Aware Mapping for Supercomputers
No full textPerformance improvements through topology aware placement for applications such as NAMD and OpenAtom are used to motivate this work. Building on these ideas, the dissertation proposes algorithms and techniques for automatic mapping of parallel applications to relieve the application developers of this burden. The effect of contention on message latencies is studied in depth to guide the design of mapping algorithms. The hop-bytes metric is proposed for the evaluation of mapping algorithms as a better metric than the previously used maximum dilation metric. The main focus of this dissertation is on developing topology aware mapping algorithms for parallel applications with regular and irregular communication patterns. The automatic mapping framework is a suite of such algorithms with capabilities to choose the best mapping for a problem with a given communication graph. The dissertation also briefly discusses completely distributed mapping techniques which will be imperative for machines of the future.Made available in DSpace on 2015-09-28T21:56:10Z (GMT). No. of bitstreams: 2
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Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDsRestricted to the U of I community idenfinitely during batch ingest of legacy ETDsU of I Only166 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2010
Automating Topology Aware Mapping for Supercomputers
No full text166 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2010.Performance improvements through topology aware placement for applications such as NAMD and OpenAtom are used to motivate this work. Building on these ideas, the dissertation proposes algorithms and techniques for automatic mapping of parallel applications to relieve the application developers of this burden. The effect of contention on message latencies is studied in depth to guide the design of mapping algorithms. The hop-bytes metric is proposed for the evaluation of mapping algorithms as a better metric than the previously used maximum dilation metric. The main focus of this dissertation is on developing topology aware mapping algorithms for parallel applications with regular and irregular communication patterns. The automatic mapping framework is a suite of such algorithms with capabilities to choose the best mapping for a problem with a given communication graph. The dissertation also briefly discusses completely distributed mapping techniques which will be imperative for machines of the future.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD
Automating Topology Aware Mapping for Supercomputers
No full textPetascale machines with hundreds of thousands of cores are being built. These machines have varying interconnect topologies and large network diameters. Computation is cheap and communication on the network is becoming the
bottleneck for scaling of parallel applications. Network contention, specifically, is becoming an increasingly important factor affecting overall performance. The broad goal of this dissertation is performance optimization of
parallel applications through reduction of network contention.
Most parallel applications have a certain communication topology. Mapping of tasks in a parallel application based on their communication graph, to the physical processors on a machine can potentially lead to performance improvements. Mapping of the communication graph for an application on to the interconnect topology of a machine while trying to localize communication is the research problem under consideration.
The farther different messages travel on the network, greater is the chance of resource sharing between messages. This can create contention on the network for networks commonly used today. Evaluative studies in this dissertation show that on IBM Blue Gene and Cray XT machines, message latencies can be severely affected under contention. Realizing this fact, application developers have started paying attention to the mapping of tasks to physical processors to minimize contention. Placement of communicating tasks on nearby physical processors can minimize the distance traveled by messages and reduce the chances of contention.
Performance improvements through topology aware placement for applications such as NAMD and OpenAtom are used to motivate this work. Building on these ideas, the dissertation proposes algorithms and techniques for automatic mapping of parallel applications to relieve the application developers of this burden. The effect of contention on message latencies is studied in depth to guide the
design of mapping algorithms. The hop-bytes metric is proposed for the evaluation of mapping algorithms as a better metric than the previously used maximum dilation metric. The main focus of this dissertation is on
developing topology aware mapping algorithms for parallel applications with regular and irregular communication patterns. The automatic mapping framework is a suite of such algorithms with capabilities to choose the best mapping for a problem with a given communication graph. The dissertation also briefly discusses completely distributed mapping techniques which will be imperative
for machines of the future.not peer reviewedSubmitted by Abhinav Bhatele ([email protected]) on 2010-07-13T23:30:49Z
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Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
AxoNN: An asynchronous, message-driven parallel framework for extreme-scale deep learning
Get PDFIn the last few years, the memory requirements to train state-of-the-art
neural networks have far exceeded the DRAM capacities of modern hardware
accelerators. This has necessitated the development of efficient algorithms to
train these neural networks in parallel on large-scale GPU-based clusters.
Since computation is relatively inexpensive on modern GPUs, designing and
implementing extremely efficient communication in these parallel training
algorithms is critical for extracting the maximum performance. This paper
presents AxoNN, a parallel deep learning framework that exploits asynchrony and
message-driven execution to schedule neural network operations on each GPU,
thereby reducing GPU idle time and maximizing hardware efficiency. By using the
CPU memory as a scratch space for offloading data periodically during training,
AxoNN is able to reduce GPU memory consumption by four times. This allows us to
increase the number of parameters per GPU by four times, thus reducing the
amount of communication and increasing performance by over 13%. When tested
against large transformer models with 12-100 billion parameters on 48-384
NVIDIA Tesla V100 GPUs, AxoNN achieves a per-GPU throughput of 49.4-54.78% of
theoretical peak and reduces the training time by 22-37 days (15-25% speedup)
as compared to the state-of-the-art.Comment: Proceedings of the IEEE International Parallel & Distributed
Processing Symposium (IPDPS). IEEE Computer Society, May 202
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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