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Enriching 3-D video games on multicores

Enriching 3-D video games on multicores

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25th IEEE international parallel and distributed Processing symposium, IPDPS 2011

作者： Cledat, Romain Kumar, Tushar Sreeram, Jaswanth Pande, Santosh School of Computer Science College of Computing Georgia Institute of Technology Atlanta GA United States School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA United States

ISBN: (纸本)9780769543857

The introduction of multicore processors on desktops and other personal computing platforms has given rise to multiple interesting end-user application possibilities. One important trend is the increased presence of resource hungry applications like gaming and multimedia applications. One of the key distinguishing factors of these applications is that they are amenable to variable semantics (ie, multiple possibilities of results) unlike traditional applications wherein a fixed, unique answer is expected. For example, varying degrees of image processing improves picture quality, different model complexities used in game physics allow different degrees of realism during game play, and so on. The goal of this paper is to demonstrate that scalable semantics in applications such as video games can be enriched with optional tasks that can be launched and thus adapt to the amount of available resources at runtime. We propose a C/C++ API that allows the programmer to define how the current semantics of a program can be opportunistically enriched, as well as the underlying runtime system that orchestrates the different computations We show how this infrastructure can be used to enrich a well known game called Quake 3. Our results show that it is possible to perform significant enrichment without degrading the application's performance by utilizing additional cores. © 2011 IEEE.

关键词： Semantics

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Multifrontal factorization of sparse SPD matrices on GPUs

Multifrontal factorization of sparse SPD matrices on GPUs

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25th IEEE international parallel and distributed Processing symposium, IPDPS 2011

作者： George, Thomas Saxena, Vaibhav Gupta, Anshul Singh, Amik Choudhury, Anamitra R. High Performance Computing Group IBM Research India New Delhi 110070 India Department of Mathematical Sciences IBM T.J. Watson Research Center Yorktown Heights NY United States Department of Electronics and Computer Engineering IIT Roorkee India

ISBN: (纸本)9780769543857

Solving large sparse linear systems is often the most computationally intensive component of many scientific computing applications. In the past, sparse multifrontal direct factorization has been shown to scale to thousands of processors on dedicated supercomputers resulting in a substantial reduction in computational time. In recent years, an alternative computing paradigm based on GPUs has gained prominence, primarily due to its affordability, power-efficiency, and the potential to achieve significant speedup relative to desktop performance on regular and structured parallel applications. However, sparse matrix factorization on GPUs has not been explored sufficiently due to the complexity involved in an efficient implementation and concerns of low GPU utilization. In this paper, we present an adaptive hybrid approach for accelerating sparse multifrontal factorization based on a judicious exploitation of the processing power of the host CPU and GPU. We present four different policies for distributing and scheduling the workload between the host CPU and the GPU, and propose a mechanism for a runtime selection of the appropriate policy for each step of sparse Cholesky factorization. This mechanism relies on auto-tuning based on modeling the best policy predictor as a parametric classifier. We estimate the classifier parameters from the available empirical computation time data such that the expected computation time is minimized. This approach is readily adaptable for using the current or an extended set of policies for different CPU-GPU combinations as well as for different combinations of dense kernels for both the CPU and the GPU. © 2011 IEEE.

关键词： Factorization

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Reader activation scheduling in multi-reader RFID systems: A study of general case

Reader activation scheduling in multi-reader RFID systems: A...

引用

25th IEEE international parallel and distributed Processing symposium, IPDPS 2011

作者： Tang, Shaojie Wang, Cheng Li, Xiang-Yang Jiang, Changjun Department of Computer Science Illinois Institute of Technology Chicago IL 60616 United States Department of Computer Science Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China

ISBN: (纸本)9780769543857

Radio frequency identification (RFID) is a technology where a reader device can "sense" the presence of a close by object by reading a tag device attached to the object. To guarantee the coverage quality, multiple RFID readers can be deployed in the given region. In this paper, we consider the problem of activation schedule for readers in a multi-reader environment. In particular, we try to design a schedule for readers to maximize the number of served tags per time-slot while avoiding various interferences. We first develop a centralized algorithm under the assumption that different readers may have different interference and interrogation radius. Next, we propose a novel algorithm which does not need any location information of the readers. Finally, we extend the previous algorithm in distributed manner in order to suit the case where no central entity exists. We conduct extensive simulations to study the performances of our proposed algorithm. And our evaluation results corroborate our theoretical analysis. © 2011 IEEE.

关键词： Graph theory

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MapReduce'11 - Proceedings of the 2nd international Workshop on MapReduce and Its Applications

MapReduce'11 - Proceedings of the 2nd International Workshop...

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2nd international Workshop on MapReduce and Its Applications, MapReduce'11, Co-located with 20th international ACM symposium on High-Performance parallel and distributed computing, HPDC 2011

ISBN: (纸本)9781450307000

The proceedings contain 9 papers. The topics discussed include: Otus: resource attribution in data-intensive clusters;Phoenix++: modular MapReduce for shared-memory systems;static type checking of hadoop MapReduce programs;exploring MapReduce efficiency with highly-distributed data;parallelizing large-scale data processing applications with data skew: a case study in product-offer matching;tall and skinny QR factorizations in MapReduce architectures;rapid parallel genome indexing with MapReduce;full-text indexing for optimizing selection operations in large-scale data analytics;MapReducing a genomic sequencing workflow;and future of MapReduce for scientific computing.

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Evaluation of simple causal message logging for large-scale fault tolerant HPC systems

Evaluation of simple causal message logging for large-scale ...

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25th IEEE international parallel and distributed Processing symposium, Workshops and Phd Forum, IPDPSW 2011

作者： Meneses, Esteban Bronevetsky, Greg Kalé, Laxmikant V. Department of Computer Science University of Illinois Urbana IL United States Center for Applied Scientific Computing Lawrence Livermore National Laboratory Livermore CA United States

ISBN: (纸本)9780769543857

The era of petascale computing brought machines with hundreds of thousands of processors. The next generation of exascale supercomputers will make available clusters with millions of processors. In those machines, mean time between failures will range from a few minutes to few tens of minutes, making the crash of a processor the common case, instead of a rarity. parallel applications running on those large machines will need to simultaneously survive crashes and maintain high productivity. To achieve that, fault tolerance techniques will have to go beyond checkpoint/restart, which requires all processors to roll back in case of a failure. Incorporating some form of message logging will provide a framework where only a subset of processors are rolled back after a crash. In this paper, we discuss why a simple causal message logging protocol seems a promising alternative to provide fault tolerance in large supercomputers. As opposed to pessimistic message logging, it has low latency overhead, especially in collective communication operations. Besides, it saves messages when more than one thread is running per processor. Finally, we demonstrate that a simple causal message logging protocol has a faster recovery and a low performance penalty when compared to checkpoint/restart. Running NAS parallel Benchmarks (CG, MG, BT and DT) on 1024 processors, simple causal message logging has a latency overhead below 5%. © 2011 IEEE.

关键词： Supercomputers

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GPGPU-based data parallel region growing algorithm for cell nuclei detection

GPGPU-based data parallel region growing algorithm for cell ...

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12th IEEE international symposium on Computational Intelligence and Informatics, CINTI 2011

作者： Szénási, Sándor Vámossy, Zoltán Kozlovszky, Miklós Óbuda University John Von Neumann Faculty of Informatics Budapest Hungary MTA SZTAKI Laboratory of Parallel and Distributed Computing Budapest Hungary

ISBN: (纸本)9781457700453

Nowadays microscopic analysis of tissue samples is done more and more by using digital imagery and special immunodiagnostic software. These are typically specific applications developed for one distinct field, but some subroutines are commonly repeated, for example several applications contain steps that can detect cell nuclei in a sample image. The aim of our research is developing a new data parallel algorithm that can be implemented even in a GPGPU environment and that is capable of counting hematoxylin eosin (HE) stained cell nuclei and of identifying their exact locations and sizes (using a variation of the region growing method). Our presentation contains the detailed description of the algorithm, the peculiarity of the CUDA implementation, and the evaluation of the created application (regarding its accuracy and the decrease in the execution time). © 2011 IEEE.

关键词： parallel algorithms

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Automatic generation of executable communication specifications from parallel applications

Automatic generation of executable communication specificati...

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25th IEEE international parallel and distributed Processing symposium, Workshops and Phd Forum, IPDPSW 2011

作者： Wu, Xing Mueller, Frank Pakin, Scott Department of Computer Science North Carolina State University Raleigh NC United States Los Alamos National Laboratory Los Alamos NM United States

ISBN: (纸本)9780769543857

Portable parallel benchmarks are widely used and highly effective for (a) the evaluation, analysis and procurement of high-performance computing (HPC) systems and (b) quantifying the potential benefits of porting applications for new hardware platforms. Yet, past techniques to synthetically parametrized hand-coded HPC benchmarks prove insufficient for today's rapidly-evolving scientific codes particularly when subject to multi-scale science modeling or when utilizing domain-specific libraries. To address these problems, this work contributes novel methods to automatically generate highly portable and customizable communication benchmarks from HPC applications. We utilize ScalaTrace, a lossless, yet scalable, parallel application tracing framework to collect selected aspects of the run-time BEHAVIOR of HPC applications. We subsequently generate benchmarks with identical run-time behavior from the collected traces in the CONCEPTUAL language, a domain-specific language that enables the expression of sophisticated communication patterns using a rich and easily understandable grammar yet compiles to ordinary C MPI. Experimental results demonstrate that the generated benchmarks are able to preserve the run-time behavior of the original applications. This ability to automatically generate performance-accurate benchmarks from parallel applications is novel and without any precedence, to our knowledge. © 2011 IEEE.

关键词： Benchmarking

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SC-OA: A secure and efficient scheme for origin authentication of interdomain routing in cloud computing networks

SC-OA: A secure and efficient scheme for origin authenticati...

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25th IEEE international parallel and distributed Processing symposium, IPDPS 2011

作者： Le, Zhongjian Xiong, Naixue Yang, Bo Zhou, Yuezhi School of Information Technology Jiangxi University of Finance and Economics Nanchang 330013 China School of Management Huazhong University of Science and Technology Wuhan 430074 China Department of Computer Science Georgia State University Atlanta GA United States Department of Computer Sci. and Tech. Tsinghua University Beijing 100084 China

ISBN: (纸本)9780769543857

IP prefix hijacking is one of the top threats in the cloud computing Internets. Based on cryptography, many schemes for preventing prefix hijacks have been proposed. Securing binding between IP prefix and its owner underlies these schemes. We believe that a scheme for securing this binding should try to satisfy these seven critical requirements: no key escrow, no other secure channel, defending against Malicious Key Issuer (MKI) in the phase of prefix announcement, defending against MKI in the phase of key issuing, no certificate, in-band delegation attestation, and in-band public key witness. In this paper, we propose a new scheme, Origin Authentication based on Self-Certified public keys (SC-OA), using self-certified public keys to authenticate origin autonomous systems. To the best of our knowledge, it is the first work for securing prefix ownership using self-certified public keys to achieve an efficient and secure scheme that satisfies all seven requirements. The analyses show that SC-OA can defend against regular prefix, sub prefix, unassigned prefix, interception-based, and MKI hijacking, and improve performance in many aspects. It will be pushed ahead to practical deployment for preventing prefix hijacks. © 2011 IEEE.

关键词： Cloud computing

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Towards an effective unified programming model for many-cores

Towards an effective unified programming model for many-core...

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25th IEEE international parallel and distributed Processing symposium, Workshops and Phd Forum, IPDPSW 2011

作者： Varbanescu, Ana Lucia Hijma, Pieter Van Nieuwpoort, Rob Bal, Henri Computing Systems Group Vrije Universiteit Amsterdam Netherlands Parallel and Distributed Systems Group Delft University of Technology Netherlands ASTRON Dwingeloo Netherlands

ISBN: (纸本)9780769543857

Building an effective programming model for many-core processors is challenging. On the one hand, the increasing variety of platforms and their specific programming models force users to take a hardware-centric approach not only for implementing parallel applications, but also for designing them. This approach diminishes portability and, eventually, limits performance. On the other hand, to effectively cope with the increased number of large-scale workloads that require parallelization, a portable, application-centric programming model is desirable. Such a model enables programmers to focus first on extracting and exploiting parallelism from their applications, as opposed to generating parallelism for specific hardware, and only second on platform-specific implementation and optimizations. In this paper, we first present a survey of programming models designed for programming three families of many-cores: general purpose many-cores (GPMCs), graphics processing units (GPUs), and the Cell/B.E. We analyze the usability of these models, their ability to improve platform programmability, and the specific features that contribute to this improvement. Next, we also discuss two types of generic models: parallelism-centric and application-centric. We also analyze their features and impact on platform programmability. Based on this analysis, we recommend two application-centric models (OmpSs and OpenCL) as promising candidates for a unified programming model for many-cores and we discuss potential enhancements for them. © 2011 IEEE.

关键词： Computer graphics

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Nearest neighbor task allocation for large-scale distributed systems

Nearest neighbor task allocation for large-scale distributed...

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international Workshop on Ad Hoc, Sensor and P2P Networks

作者： Tada, Harumasa Faculty of Education Kyoto University of Education 1 Fukaskusa-Fujinomori-cho Fushimi-ku Kyoto 612-8522 Japan

ISBN: (纸本)9780769543499

In this paper, we consider distributed task allocation in distributed systems. In order to improve the performance, using load information of nodes is promising. In reality, however, it is common that load information is not up to date when it is used. Load information may be updated only periodically, or the communication delay for a task to move to other node makes load information out of date. The performance of task allocation schemes is significantly damaged if the load information is old. In order to tackle this problem, we introduce the nearest neighbor approach which is originally proposed for parallel computing. Restricting the communication to between neighboring nodes, the effect of communication delay is suppressed. Simulation results showed that our proposed scheme suppresses the effect of old load information and shows better performance than a previously proposed scheme.

关键词： load balancing old load information parallel computing task assignment

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