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P-sync: a photonically enabled architecture for efficient non-local data access

May 20, 2013
  |
Conference Paper
Author:
David J. Whelihan
…
Published in:
ICPADS 2013: 27th Int. Conf. on Parallel and Distributed Systems, 20-24 May 2013.
Topic:
supercomputing
R&D area:

Summary

Communication in multi- and many-core processors has long been a bottleneck to performance due to the high cost of long-distance electrical transmission. This difficulty has been partially remedied by architectural constructs such as caches and novel interconnect topologies, albeit at a steep cost in terms of complexity. Unfortunately, even these measures are rendered ineffective by certain kinds of communication, most notably scatter and gather operations that exhibit highly non-local data access patterns. Much work has gone into examining how the increased bandwidth density afforded by chip-scale silicon photonic interconnect technologies affects computing, but photonics have additional properties that can be leveraged to greatly accelerate performance and energy efficiency under such difficult loads. This paper describes a novel synchronized global photonic bus and system architecture called P-sync that uses photonics' distance independence to greatly improve performance on many important applications previously limited by electronic interconnect. The architecture is evaluated in the context of a non-local yet common application: the distributed Fast Fourier Transform. We show that it is possible to achieve high efficiency by tightly balancing computation and communication latency in P-sync and achieve upwards of a 6x performance increase on gather patterns, even when bandwidth is equalized.
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Summary

Communication in multi- and many-core processors has long been a bottleneck to performance due to the high cost of long-distance electrical transmission. This difficulty has been partially remedied by architectural constructs such as caches and novel interconnect topologies, albeit at a steep cost in terms of complexity. Unfortunately, even these...

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P-sync: a photonically enabled architecture for efficient non-local data access

Creating a cyber moving target for critical infrastructure applications using platform diversity

January 28, 2012
  |
Journal Article
Author:
Hamed Okhravi
…
Published in:
Int. J. of Critical Infrastructure Protection, Vol. 5, No. 1, March 2012, pp. 30-39.
Topic:
systems architecture
R&D area:
R&D group:

Summary

Despite the significant effort that often goes into securing critical infrastructure assets, many systems remain vulnerable to advanced, targeted cyber attacks. This paper describes the design and implementation of the Trusted Dynamic Logical Heterogeneity System (TALENT), a framework for live-migrating critical infrastructure applications across heterogeneous platforms. TALENT permits a running critical application to change its hardware platform and operating system, thus providing cyber survivability through platform diversity. TALENT uses containers (operating-system-level virtualization) and a portable checkpoint compiler to create a virtual execution environment and to migrate a running application across different platforms while preserving the state of the application (execution state, open files and network connections). TALENT is designed to support general applications written in the C programming language. By changing the platform on-the-fly, TALENT creates a cyber moving target and significantly raises the bar for a successful attack against a critical application. Experiments demonstrate that a complete migration can be completed within about one second.
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Summary

Despite the significant effort that often goes into securing critical infrastructure assets, many systems remain vulnerable to advanced, targeted cyber attacks. This paper describes the design and implementation of the Trusted Dynamic Logical Heterogeneity System (TALENT), a framework for live-migrating critical infrastructure applications across heterogeneous platforms. TALENT permits a running...

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Creating a cyber moving target for critical infrastructure applications using platform diversity

Fundamental Questions in the Analysis of Large Graphs

January 1, 2012
  |
Book Chapter
Author:
Jeremy Kepner
…
Published in:
Graph Algorithms in the Language of Linear Algebra, pp. 353-357.
Topic:
graph processing
R&D area:
R&D group:

Summary

Graphs are a general approach for representing information that spans the widest possible range of computing applications. They are particularly important to computational biology, web search, and knowledge discovery. As the sizes of graphs increase, the need to apply advanced mathematical and computational techniques to solve these problems is growing dramatically. Examining the mathematical and computational foundations of the analysis of large graphs generally leads to more questions than answers. This book concludes with a discussion of some of these questions.
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Summary

Graphs are a general approach for representing information that spans the widest possible range of computing applications. They are particularly important to computational biology, web search, and knowledge discovery. As the sizes of graphs increase, the need to apply advanced mathematical and computational techniques to solve these problems is growing...

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Fundamental Questions in the Analysis of Large Graphs

A knowledge-based operator for a genetic algorithm which optimizes the distribution of sparse matrix data

January 1, 2012
  |
Book Chapter
Author:
Una-May O'Reilly
…
Published in:
Parallel Architectures and Bioinspired Algorithms
Topic:
algorithms
R&D area:
R&D group:

Summary

We present the Hogs and Slackers genetic algorithm (GA) which addresses the problem of improving the parallelization efficiency of sparse matrix computations by optimally distributing blocks of matrices data. The performance of a distribution is sensitive to the non-zero patterns in the data, the algorithm, and the hardware architecture. In a candidate distributions the Hogs and Slackers GA identifies processors with many operations – hogs, and processors with fewer operations – slackers. Its intelligent operation-balancing mutation operator then swaps data blocks between hogs and slackers to explore a new data distribution.We show that the Hogs and Slackers GA performs better than a baseline GA. We demonstrate Hogs and Slackers GA’s optimization capability with an architecture study of varied network and memory bandwidth and latency.
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Summary

We present the Hogs and Slackers genetic algorithm (GA) which addresses the problem of improving the parallelization efficiency of sparse matrix computations by optimally distributing blocks of matrices data. The performance of a distribution is sensitive to the non-zero patterns in the data, the algorithm, and the hardware architecture. In...

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A knowledge-based operator for a genetic algorithm which optimizes the distribution of sparse matrix data

Linear algebraic notation and definitions

January 1, 2012
  |
Book Chapter
Author:
Eric I. Robinson
…
Published in:
Graph Algorithms in the Language of Linear Algebra, pp. 13-18.
Topic:
algorithms
R&D area:
R&D group:

Summary

This chapter presents notation, definitions, and conventions for graphs, matrices, arrays, and operations upon them.
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Summary

This chapter presents notation, definitions, and conventions for graphs, matrices, arrays, and operations upon them.

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Linear algebraic notation and definitions

Creating a cyber moving target for critical infrastructure applications

March 19, 2011
  |
Conference Paper
Author:
Hamed Okhravi
…
Published in:
5th IFIP Int. Conf. on Critical Infrastructure Protection, ICCIP 2011, 19-21 March 2011.
Topic:
systems architecture
R&D area:
R&D group:

Summary

Despite the significant amount of effort that often goes into securing critical infrastructure assets, many systems remain vulnerable to advanced, targeted cyber attacks. This paper describes the design and implementation of the Trusted Dynamic Logical Heterogeneity System (TALENT), a framework for live-migrating critical infrastructure applications across heterogeneous platforms. TALENT permits a running critical application to change its hardware platform and operating system, thus providing cyber survivability through platform diversity. TALENT uses containers (operating-system-level virtualization) and a portable checkpoint compiler to create a virtual execution environment and to migrate a running application across different platforms while preserving the state of the application (execution state, open files and network connections). TALENT is designed to support general applications written in the C programming language. By changing the platform on-the-fly, TALENT creates a cyber moving target and significantly raises the bar for a successful attack against a critical application. Experiments demonstrate that a complete migration can be completed within about one second.
READ LESS

Summary

Despite the significant amount of effort that often goes into securing critical infrastructure assets, many systems remain vulnerable to advanced, targeted cyber attacks. This paper describes the design and implementation of the Trusted Dynamic Logical Heterogeneity System (TALENT), a framework for live-migrating critical infrastructure applications across heterogeneous platforms. TALENT permits...

READ MORE
Creating a cyber moving target for critical infrastructure applications

TALENT: dynamic platform heterogeneity for cyber survivability of mission critical applications

October 29, 2010
  |
Conference Paper
Author:
Hamed Okhravi
…
Published in:
Proc. Secure and Resilient Cyber Architecture Conf., SRCA, 29 October 2010.
Topic:
systems architecture
R&D area:
R&D group:

Summary

Despite the significant amount of effort that often goes into securing mission critical systems, many remain vulnerable to advanced, targeted cyber attacks. In this work, we design and implement TALENT (Trusted dynAmic Logical hEterogeNeity sysTem), a framework to live-migrate mission critical applications across heterogeneous platforms. TALENT enables us to change the hardware and operating system on top of which a sensitive application is running, thus providing cyber survivability through platform diversity. Using containers (a.k.a. operating system-level virtualization) and a portable checkpoint compiler, TALENT creates a virtual execution environment and migrates a running application across different platforms while preserving the state of the application. The state, here, refers to the execution state of the process as well as its open files and sockets. TALENT is designed to support a general C application. By changing the platform on-the-fly, TALENT creates a moving target against cyber attacks and significantly raises the bar for a successful attack against a critical application. Our measurements show that a full migration can be completed in about one second.
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Summary

Despite the significant amount of effort that often goes into securing mission critical systems, many remain vulnerable to advanced, targeted cyber attacks. In this work, we design and implement TALENT (Trusted dynAmic Logical hEterogeNeity sysTem), a framework to live-migrate mission critical applications across heterogeneous platforms. TALENT enables us to change...

READ MORE
TALENT: dynamic platform heterogeneity for cyber survivability of mission critical applications

Hogs and slackers: using operations balance in a genetic algorithm to optimize sparse algebra computation on distributed architectures

October 1, 2010
  |
Journal Article
Author:
Una-May O'Reilly
…
Published in:
Parallel Comput., Vol. 36, No. 10-11, October-November 2010, pp. 635-644.
Topic:
algorithms
R&D area:
R&D group:

Summary

We present a framework for optimizing the distributed performance of sparse matrix computations. These computations are optimally parallelized by distributing their operations across processors in a subtly uneven balance. Because the optimal balance point depends on the non-zero patterns in the data, the algorithm, and the underlying hardware architecture, it is difficult to determine. The Hogs and Slackers genetic algorithm (GA) identifies processors with many operations - hogs, and processors with few operations - slackers. Its intelligent operation-balancing mutation operator swaps data blocks between hogs and slackers to explore new balance points. We show that this operator is integral to the performance of the genetic algorithm and use the framework to conduct an architecture study that varies network specifications. The Hogs and Slackers GA is itself a parallel algorithm with near linear speedup on a large computing cluster.
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Summary

We present a framework for optimizing the distributed performance of sparse matrix computations. These computations are optimally parallelized by distributing their operations across processors in a subtly uneven balance. Because the optimal balance point depends on the non-zero patterns in the data, the algorithm, and the underlying hardware architecture, it...

READ MORE
Hogs and slackers: using operations balance in a genetic algorithm to optimize sparse algebra computation on distributed architectures
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