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ECM at Work

引用

18th international conference on theory and Application of Cryptology and Information Security (ASIACRYPT)

作者： Bos, Joppe W. Kleinjung, thorsten Microsoft Res One Microsoft Way Redmond WA 98052 USA Ecole Polytech Fed Lausanne Lab Cryptol Algorithms Lausanne Switzerland

ISBN: (纸本)9783642349614;9783642349607

the performance of the elliptic curve method (ECM) for integer factorization plays an important role in the security assessment of RSA-based protocols as a cofactorization tool inside the number field sieve. the efficient arithmetic for Edwards curves found an application by speeding up ECM. We propose techniques based on generating and combining addition-subtracting chains to optimize Edwards ECM in terms of both performance and memory requirements. this makes our approach very suitable for memory-constrained devices such as graphics processing units (GPU). For commonly used ECM parameters we are able to lower the required memory up to a factor 55 compared to the state-of-the-art Edwards ECM approach. Our ECM implementation on a GTX 580 GPU sets a new throughput record, outperforming the best GPU, CPU and FPGA results reported in literature.

关键词： Elliptic curve factorization cofactorization addition-subtraction chains twisted Edwards curves parallel architectures

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GPU-based biclustering for neural information processing

GPU-based biclustering for neural information processing

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19th international conference on Neural Information processing, ICONIP 2012

作者： Lo, Alan W. Y. Liu, Benben Cheung, Ray C. C. Department of Electronic Engineering City University of Hong Kong Hong Kong Hong Kong

ISBN: (纸本)9783642344992

this paper presents an efficient mapping of geometric biclustering (GBC) algorithm for neural information processing on Graphical processing Unit (GPU). the proposed designs consist of five different versions which extensively study the use of memory components on the GPU board for mapping the GBC algorithm. GBC algorithm is used to find any maximal biclusters, which are common patterns in each column in the neural processing and gene microarray data. A microarray commonly involves a huge number of data, such as thousands of rows by thousands of columns so that finding the maximal biclusters involves intensive computation. the advantage of GPU is its ability of parallel computing which means that for those independent procedures, they can be carried out at the same time. Experimental results show that the GPU-based GBC could reduce the processing time largely due to the parallel computing of GPU, and its scalability. As an example, GBC algorithm involves a large number of AND operations which utilize the parallel GPU computations, that can be further practically used for other neural processing algorithms. © 2012 Springer-Verlag.

关键词： Graphics processing unit

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Interaction List Compression in Large parallel Particle Simulations on Multicore Systems

Interaction List Compression in Large Parallel Particle Simu...

引用

Euromicro conference on parallel, Distributed and Network-Based processing

作者： Gudula Runger Michael Schwind Chemnitz University of Technology Chemnitz Germany

Many particle simulation codes use interaction lists to store interacting particles. Depending on the physical parameters of the simulations those interaction lists may occupy a large amount of physical memory, which may limit the number of particles of the simulation. this article discusses several methods that try to reduce the size of interaction lists while maintaining the number of particle interactions per second or even increase it. Different techniques are discussed for a parallel shared memory algorithm on multicore architectures. On those architectures, the memory bandwidth is shared by multiple cores. Since the interaction list is a large shared data structure, it cannot be stored in CPU caches and has to be streamed into the processor several times. A reduction of the size of the interaction list will therefore reduce the number of elements to be reloaded resulting in more efficient implementations.

关键词： Force Multicore processing Runtime Indexes Memory management parallel algorithms Data models

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Optimization Techniques and Performance Analyses of Two Life Science algorithms for Novel GPU architectures

Optimization Techniques and Performance Analyses of Two Life...

引用

Euromicro conference on parallel, Distributed and Network-Based processing

作者： David Dilch Eduard Mehofer Research Group Scientific Computing Faculty of Computer Science University of Technology Vienna Austria

In this paper we evaluate two life science algorithms, namely Needleman-Wunsch sequence alignment and Direct Coulomb Summation, for GPUs. Whereas for Needleman-Wunsch it is difficult to get good performance numbers, Direct Coulomb Summation is particularly suitable for graphics cards. We present several optimization techniques, analyze the theoretical potential of the optimizations with respect to the algorithms, and measure the effect on execution times. We target the recent NVIDIA Fermi architecture to evaluate the performance impacts of novel hardware features like the cache subsystem on optimizing transformations. We compare the execution times of CUDA and OpenCL code versions for Fermi and predecessor models with parallel OpenMP versions executed on the main CPU.

关键词： Graphics processing unit Kernel Optimization Instruction sets Hardware Computer architecture Synchronization

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A GPU-based high-throughput image retrieval algorithm 5

A GPU-based high-throughput image retrieval algorithm

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5th Workshop on General-Purpose Computation on Graphics processing Units, GPGPU-5 - Held in Cooperation with ACM ASPLOS XVII

作者： Zhu, Feiwen Chen, Peng Yang, Donglei Zhang, Weihua Chen, Haibo Zang, Binyu State Key Lab. of ASIC and System Fudan University China Parallel Processing Institute Fudan University China Architecture Key Lab. Institute of Computing Technology Chinese Academy of Sciences China

ISBN: (纸本)9781450312332

With the development of Internet and cloud computing, multimedia data, such as images and videos, has become one of the most common data types being processed. As the scale of multimedia data being still increasing, it is vitally important to efficiently extract useful information from such a huge amount of multimedia data. However, due to the complexity of the core algorithms, multimedia retrieval applications are not only data intensive but also computationally intensive. therefore, it has been a major challenge to accelerate the processing speed of such applications to satisfy the real-time requirement. As Graphic processing Unit (GPU) has entered the general-propose computing domain (GPGPU), it has become one of the most popular accelerators for the applications with real-time requirements. In this paper, we parallelize a widely-used image retrieval algorithm called SURF on GPGPU, which is the core algorithm for many video and image retrieval applications. We first analyze the parallelism within SURF to guarantee that there are sufficient tasks being mapped to the large-scale computation resources in GPGPU. We then exploit some inherent GPGPU characteristics, such as 2D memory, to further boost the performance. Finally, we provide some optimization to the cooperation between CPU and GPGPU, which is generally ignored in previous designs. Experimental results show that our parallelization and optimization achieve a throughput of 340.5 frames/s on a NVIDIA GTX295 GPGPU, which is 15X faster than the maximal optimized CPU version. Compared to CUDA SURF, a state-of-the-art parallelization of SURF on GPGPU, our system achieves a speedup by a factor of 2.3X. © 2012 ACM.

关键词： Graphics processing unit

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Mstar: A New Two Level Interconnection Network

Mstar: A New Two Level Interconnection Network

引用

8th international conference on Distributed Computing and Internet Technologies (ICDCIT 2012)

作者： Adhikari, Nibedita Tripathy, C. R. VSS Univ Technol Dept CSE Burla Sambalpur Orissa India

ISBN: (纸本)9783642280726;9783642280733

In the literature various two level interconnection networks are proposed using hypercubes or star graphs. In this paper, a new two level interconnection network topology called the Metastar denoted as Mstar(k,m) is introduced. the proposed network takes the star graph as basic building blocks. Here, the network at the lower level is a star but at the higher level the network is a cube. Its various topological parameters such as packing density, degree, diameter, cost, average distance and hamiltonicity are investigated. Message routing and broadcasting algorithms are also proposed. Performance analysis in terms of topological parameters is done and the proposed network is proved to be a suitable candidate for large scale computing.

关键词： parallel processing interconnection network topological parameters

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A spiking neural P system simulator based on CUDA

A spiking neural P system simulator based on CUDA

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12th international conference on Membrane Computing, CMC 2011

作者： Cabarle, Francis George C. Adorna, Henry Martínez, Miguel A. Algorithms and Complexity Lab. Department of Computer Science University of the Philippines Diliman Diliman 1101 Quezon City Philippines Research Group on Natural Computing Department of Computer Science and Artificial Intelligence University of Seville Avda. Reina Mercedes s/n 41012 Sevilla Spain

ISBN: (纸本)9783642280238

In this paper we present a Spiking Neural P system (SNP system) simulator based on graphics processing units (GPUs). In particular we implement the simulator using NVIDIA CUDA enabled GPUs. the massively parallel architecture of current GPUs is very suitable for the maximally parallel computations of SNP systems. We simulate a wider variety of SNP systems, after presenting a previous work on SNP system matrix representation which led to their simulation in GPUs, and the simulation algorithm included here. Finally, we compare and present the performance speedups of the CPU-GPU based simulator over the CPU only simulator. © 2012 Springer-Verlag.

关键词： Graphics processing unit

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Comparison between parallel and distributed molecular dynamics simulations of Lennard-Jones systems

Comparison between parallel and distributed molecular dynami...

引用

IEEE international conference on Intelligent Computer Communication and processing (ICCP)

作者： Vlad Baja Dorian Gorgan Titus Beu Computer Science Department Technical University of Cluj Napoca Cluj-Napoca Romania Faculty of Physics University Babes-Bolyai Cluj-Napoca Romania

this paper concerns mainly with parallel and distributed implementations of molecular dynamics simulations of the Lennard-Jones potential model. the reported research work studies and experiments different algorithms and parallelization techniques for shared memory and message passing architectures, and the programs are executed on single-core processors, multi-core processors, GPU, and GPU cluster. the solution based on efficient versions of the neighbor list algorithm and space division technique is further discussed. the obtained speedups for multi-core processor, GPU, and GPU cluster, relative to the single-core processor implementation of the program, are analyzed, and the advantages of the algorithms are highlighted.

关键词： Computational modeling Graphics processing units Multicore processing Computers Arrays Force Message systems

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Auto-tuning interactive ray tracing using an analytical GPU architecture model 5

Auto-tuning interactive ray tracing using an analytical GPU ...

引用

5th Workshop on General-Purpose Computation on Graphics processing Units, GPGPU-5 - Held in Cooperation with ACM ASPLOS XVII

作者： Ganestam, Per Doggett, Michael Lund University Sweden

ISBN: (纸本)9781450312332

this paper presents a method for auto-tuning interactive ray tracing on GPUs using a hardware model. Getting full performance from modern GPUs is a challenging task. Workloads which require a guaranteed performance over several runs must select parameters for the worst performance of all runs. Our method uses an analytical GPU performance model to predict the current frame's rendering time using a selected set of parameters. these parameters are then optimised for a selected frame rate performance on the particular GPU architecture. We use auto-tuning to determine parameters such as phong shading, shadow rays and the number of ambient occlusion rays. We sample a priori information about the current rendering load to estimate the frame workload. A GPU model is run iteratively using this information to tune rendering parameters for a target frame rate. We use the OpenCL API allowing tuning across different GPU architectures. Our auto-tuning enables the rendering of each frame to execute in a predicted time, so a target frame rate can be achieved even with widely varying scene complexities. Using this method we can select optimal parameters for the current execution taking into account the current viewpoint and scene, achieving performance improvements over predetermined parameters. © 2012 ACM.

关键词： Graphics processing unit

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SIMT Microscheduling: Reducing thread Stalling in Divergent Iterative algorithms

SIMT Microscheduling: Reducing Thread Stalling in Divergent ...

引用

Euromicro conference on parallel, Distributed and Network-Based processing

作者： Steffen Frey Guido Reina thomas Ertl Visualization Research Center University of Stuttgart Stuttgart Germany

the global scheduler of a current GPU distributes thread blocks to symmetric multiprocessors (SM), which schedule threads for execution with the granularity of a warp. threads in a warp execute the same code path in lockstep, which potentially leads to a large amount of wasted cycles for divergent control flow. In order to overcome this general issue of SIMT architectures, we propose techniques to relax divergence on the fly within a computation kernel in order to achieve a much higher total utilization of processing cores. We propose techniques for branch and loop divergence (which may also be combined) switching to suitable tasks during a GPU kernel run every time divergence occurs. Our newly introduced techniques can easily be applied to arbitrary iterative algorithms and we evaluate the performance and effectiveness of our approach exemplarily via synthetic and real world applications.

关键词： Instruction sets Context Switches Kernel Graphics processing unit Memory management Hardware

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