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A GPU-based WFST Decoder with Exact Lattice Generation 19

A GPU-based WFST Decoder with Exact Lattice Generation

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19th Annual conference of the international-Speech-Communication-Association (INTERSPEECH 2018)

作者： Chen, Zhehuai Luitjens, Justin Xu, Hainan Wang, Yiming Povey, Daniel Khudanpur, Sanjeev Shanghai Jiao Tong Univ Dept Comp Sci & Engn SpeechLab Shanghai Peoples R China NVIDIA Santa Clara CA USA Johns Hopkins Univ Ctr Language & Speech Proc Baltimore MD 21218 USA

ISBN: (纸本)9781510872219

We describe initial work on an extension of the Kaldi toolkit that supports weighted finite-state transducer (WFST) decoding on Graphics processing Units (GPUs). We implement token recombination as an atomic GPU operation in order to fully parallelize the Viterbi beam search, and propose a dynamic load balancing strategy for more efficient token passing scheduling among GPU threads. We also redesign the exact lattice generation and lattice pruning algorithms for better utilization of the GPUs. Experiments on the Switchboard corpus show that the proposed method achieves identical 1-best results. and lattice quality in recognition and confidence measure tasks, while running 3 to 15 times faster than the single process Kaldi decoder. the above results are reported on different GPU architectures. Additionally we obtain a 46-fold speedup with sequence parallelism and multi-process service (MPS) in GPU.

关键词： ASR Decoder parallel Computing WFST GPU Lattice processing Confidence Measure

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Implementation of beamforming for large-scale circular array sonar based on parallel FIR filter structure in FPGA 18th

Implementation of beamforming for large-scale circular array...

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18th international conference on algorithms and architectures for parallel processing - ICA3PP 2018 Collocated Workshops: ICA3PP 2018 Workshop on Intelligent algorithms for Large-scale Complex Optimization Problems, IALCOP 2018, ICA3PP 2018 Workshop on Security and Privacy in Data processing, SPDP 2018

作者： Wang, Jun Jiao, Junsheng Science and Technology on Sonar Laboratory Hangzhou Applied Acoustics Research Institute Hangzhou China

ISBN: (纸本)9783030052331

In this paper, the directivity of the circular array is analyzed, real-time beamforming algorithm of circular array in frequency domain similar to parallel FIR filter structure is proposed by using the characteristic of the same directivity in different directions and the characteristic of steer vector symmetry. the coefficients of parallel FIR (Finite Impulse Response) filters are constant, while the steer vector of each frequency in the beamforming algorithm is variable, so the coefficients (steer vector) of the beamforming parallel filter need to be dynamically changed according to the frequency points. For frequency domain beamforming of high frequency large-scale circular array sonar, this algorithm only needs two shift registers, complex multipliers which is half the number of elements used in beamforming and a few logic resources to calculate steer vector in FPGA (Field Programmable Gate Array), and the algorithm can run at a higher working frequency. the lake-trial result shows that this parallel algorithm satisfies the real-time requirements of high-frequency large-scale circular array sonar, and the sonar has good azimuth resolution and detection performance. © Springer Nature Switzerland AG 2018.

关键词： Beamforming

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Intrusion Detection System Using Machine Learning Techniques for Increasing Accuracy and Distributed & parallel Approach for Increasing Efficiency

Intrusion Detection System Using Machine Learning Techniques...

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international conference on Computing Communication Control and Automation (ICCUBEA)

作者： Abhijit D. Jadhav Vidyullatha Pellakuri Department of Computer Science & Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram A.P. India

ISBN: (数字)9781728140421

ISBN: (纸本)9781728140438

In the current era of wide use of internet by the users across the globe, the data generated and its security both are the important issues. Hence, in any network to prevent the malicious activities from the intrusions, the early and correct detection of intruders is important. For that we are using Intrusion Detection systems (IDS), developed with many effective algorithms which are helping us to get rid of these attacks. But, sometimes these systems do respond with the detection of intruders who are in real, not the intruders, but the normal users. this makes these users difficult to continue with the normal communication and can be prevented from accessing the important services over the World Wide Web. Similarly, not tolerable at all, when it's false negative i.e. intruder is allowed to enter into network traffic being a normal user, as it may cost to an organization to the extent of being demolished their future. though the percentage of these false positives and false negatives is less, it is creating issues in many important services. For that we can have a machine learning techniques which can effectively detect intrusions in the system without creating obstacles of false positives and false negatives, also we are proposing it for the online streamed data. Also, this IDS implementation using machine learning techniques is proposed with Distributed & parallel approach for simultaneous processing of network traffic data by these different machine learning techniques. this approach enables us to implement this IDS design for Online streamed data for faster detection i.e. increasing efficiency of IDS.

关键词： accuracy false negatives false positives intrusion detection machine learning techniques

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Porting and optimizing VASP on the SW26010 18th

Porting and optimizing VASP on the SW26010

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作者： Li, Leisheng Sun, Qiao Liu, Xin Wu, Changmao Zhao, Haitao Zhang, Changyou Laboratory of Parallel Software and Computational Science Institute of Software Chinese Academy of Sciences Beijing China National Research Centre of Parallel Computer Engineering and Technology WuxiJiangsu China

ISBN: (纸本)9783030052331

VASP (Vienna Ab initio Simulation Package) is a prevalent first-principle software framework. It is so widely used that its runtime usually dominates the usage of current supercomputers. the porting and optimization of VASP to the Sunway TaihuLight supercomputer, a newly heterogeneous many-core platform based on SW26010 CPU, becomes of great importance. In this paper, we focus on the challenges in porting and optimizing VASP on the SW26010 CPU. Optimizations on three types of time-consuming kernels, which include matrix operations, FFT, and certain domain-specific computing primitives, are carried out base on thorough performance profiling. the experimental results are shown by the case of RELAX, where speedup of 2.90x and 4.48x is sustained respectively for both of the iterative diagonalization methods in VASP, RMM-DIIS (RMM) and block Davidson (DAV). © Springer Nature Switzerland AG 2018.

关键词： Density functional theory

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PolySA: Polyhedral-Based Systolic Array Auto-Compilation 18

PolySA: Polyhedral-Based Systolic Array Auto-Compilation

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37th IEEE/ACM international conference on Computer-Aided Design (ICCAD)

作者： Cong, Jason Wang, Jie Univ Calif Los Angeles Los Angeles CA 90024 USA

ISBN: (纸本)9781450359504

Automatic systolic array generation has long been an interesting topic due to the need to reduce the lengthy development cycles of manual designs. Existing automatic systolic array generation approach builds dependency graphs from algorithms, and iteratively maps computation nodes in the graph into processing elements (PEs) with time stamps that specify the sequences of nodes that operate within the PE. there are a number of previous works that implemented the idea and generated designs for ASICs. However, all of these works relied on human intervention and usually generated inferior designs compared to manual designs. In this work, we present our ongoing compilation framework named PolySA which leverages the power of the polyhedral model to achieve the end-to-end compilation for systolic array architecture on FPGAs. PolySA is the first fully automated compilation framework for generating high-performance systolic array architectures on the FPGA leveraging recent advances in high-level synthesis. We demonstrate PolySA on two key applications matrix multiplication and convolutional neural network. PolySA is able to generate optimal designs within one hour with performance comparable to state-of-the-art manual designs.

关键词： Scattering Field programmable gate arrays Manuals Arrays parallel processing Two dimensional displays

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16th international conference on algorithms and architectures for parallel processing, ICA3PP 2016

16th International Conference on Algorithms and Architecture...

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16th international conference on algorithms and architectures for parallel processing, ICA3PP 2016

ISBN: (纸本)9783319495828

the proceedings contain 52 papers. the special focus in this conference is on parallel, Distributed architectures, Software Systems, Programming, Distributed, Network-Based Computing, Big Data, Its Applications, parallel, Distributed algorithms, Performance Modeling and Evaluation. the topics include: Optimizing execution performance by automatic query relaxation and queue scheduling;hardware-based sequential consistency violation detection made simpler;optimized mapping spiking neural networks onto network-on-chip;a portable lock-free bounded queue;creating distributed execution plans with bobolangng;a new scalable approach for distributed metadata in HPC;enabling android-based devices to high-end GPGPUs;3-additive approximation algorithm for multicast time in 2D torus networks;a novel optical high-radix switch architecture for 3D integration;a platform based on microclouds for neighborhood services;impact of shutdown techniques for energy-efficient cloud data centers;implement and optimization of indoor positioning system based on Wi-Fi signal;road segment information based named data networking for vehicular environments;energy-aware query processing on a parallel database cluster node;current flow betweenness centrality with apache spark;light loss-less data compression, with GPU implementation;a GPU-based backtracking algorithm for permutation combinatorial problems;scaling DBSCAN-like algorithms for event detection systems in twitter;towards parallel CFD computation for the ADAPT framework;leveraging the performance of LBM-HPC for large sizes on GPUs using ghost cells;locality of computation for stencil optimization;an efficient implementation of LZW compression in the FPGA and GPU-based heterogeneous coding architecture for HEVC.

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Hyaline: A Transparent Distributed Computing Framework for CUDA

Hyaline: A Transparent Distributed Computing Framework for C...

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international conference for Convergence of Technology (I2CT)

作者： Akshat Jain Owais Kazi Raviraj Joshi Shraddha Basantwani Yogita Bang Rahul Khengare Computer Engineering PICT Pune Computer Science IIT Madras

ISBN: (数字)9781538680759

ISBN: (纸本)9781538680766

the GPU usually handles the homogenous data parallel work, by taking advantage of its massive number of cores. In most of the applications, we use CUDA programming for utilizing the power of GPU. In data intensive high computational applications like neural networks, utilizing the GPU on a single machine is time consuming. Instead if multiple GPUs are used in a network the amount of time required will be significantly reduced. Traditionally to enable a set of program to be run in a distributed environment, programmer has to accordingly design components to make his system dynamic and resilient to changes in number of systems in cluster, which is a daunting task. this work distribution can be a poor solution as it may underutilize the GPUsIn our approach, we developed a framework which transparently distributes data parallel kernels across multiple GPUs in a distributed network. the programmer is responsible for developing a single data parallel kernel in CUDA while the framework automatically distributes the workload across an arbitrary set of CUDA enabled GPUs. Depending on current workload on GPUs and the amount of data to be processed optimal distribution is done. the goal is to maximally utilize the available resources with minimal programming complexity. the systems not compatible with CUDA can also utilize our solution. We expect our framework to reduce the processing time along with simplifying the task of programmers.

关键词： Graphics processing units Kernel Distributed databases Computational modeling Programming Task analysis Computer architecture

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Performance Assessment of the Incremental Strong Constraints 4DVAR Algorithm in ROMS 12th

Performance Assessment of the Incremental Strong Constraints...

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12th international conference on parallel processing and Applied Mathematics (PPAM)

作者： D'Amore, Luisa Arcucci, Rossella Li, Yi Montella, Raffaele Moore, Andrew Phillipson, Luke Toumi, Ralf Univ Naples Federico II Naples Italy Imperial Coll London London England Univ Naples Parthenope Naples Italy Univ Santa Cruz Santa Cruz CA USA

ISBN: (纸本)9783319780542;9783319780535

We consider the Incremental Strong constraint 4D VARiational (IS4DVAR) algorithm for data assimilation implemented in ROMS with the aim to study its performance in terms of strong scaling scalability on computing architectures such as a cluster of CPUs. We consider realistic test cases with data collected in enclosed and semi enclosed seas, namely, Caspian sea, West Africa/Angola, as well as data collected into the California bay. the computing architecture we use is currently available at Imperial College London. the analysis allows us to highlight that the ROMS-IS4DVAR performance on emerging architectures depends on a deep relation among the problems size, the domain decomposition approach and the computing architecture characteristics.

关键词： Data assimilation 4DVAR algorithm Performance analysis parallel algorithm

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algorithms for Forward and Backward Solution of the Fokker-Planck Equation in the Heliospheric Transport of Cosmic Rays 12th

Algorithms for Forward and Backward Solution of the Fokker-P...

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12th international conference on parallel processing and Applied Mathematics (PPAM)

作者： Wawrzynczak, Anna Modzelewska, Renata Gil, Agnieszka Siedlce Univ Inst Comp Sci Siedlce Poland Siedlce Univ Inst Math & Phys Siedlce Poland

ISBN: (纸本)9783319780245;9783319780238

Motion of charged particles in an inhomogeneous turbulent medium as magnetic field is described by partial differential equations of the Fokker-Planck-Kolmogorov type. We present an algorithm of numerical solution of the four-dimensional Fokker-Planck equation in three-dimensional spherical coordinates system. the algorithm is based on Monte Carlo simulations of the stochastic motion of quasi-particles guided by the set of stochastic differential equations corresponding to the Fokker-Planck equation by the Ito formalism. We present the parallel algorithm in Julia programming language. We simulate the transport of cosmic rays in the heliosphere considering the full three-dimensional diffusion tensor. We compare forward-and backward-in-time solutions of the transport equation and discuss its computational advantages and disadvantages.

关键词： Numerical algorithms Fokker-Planck equation Stochastic differential equations Cosmic ray transport Julia parallel programming

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RiBoSOM: Rapid Bacterial Genome Identification Using Self-Organizing Map implemented on the Synchoros SiLago Platform 18

RiBoSOM: Rapid Bacterial Genome Identification Using Self-Or...

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18th international conference on Embedded Computer Systems - architectures, Modeling, and Simulation (SAMOS)

作者： Yang, Yu Stathis, Dimitrios Sharma, Prashant Paul, Kolin Hemani, Ahmed Grabherr, Manfred Ahmad, Rafi Royal Inst Technol KTH Stockholm Sweden Indian Inst Technol Delhi Delhi India Uppsala Univ Uppsala Sweden Inland Norway Univ Appl Sci Hamar Norway

ISBN: (纸本)9781450364942

Artificial Neural Networks have been applied to many traditional machine learning applications in image and speech processing. More recently, ANNs have caught attention of the bioinformatics community for their ability to not only speed up by not having to assemble genomes but also work with imperfect data set with duplications. ANNs for bioinformatics also have the added attraction of better scaling for massive parallelism compared to traditional bioinformatics algorithms. In this paper, we have adapted Self-organizing Maps for rapid identification of bacterial genomes called BioSOM. BioSOM has been implemented on a design of two coarse grain reconfigurable fabrics customized for dense linear algebra and streaming scratchpad memory respectively. these fabrics are implemented in a novel synchoros VLSI design style that enables composition by abutment. the synchoricity empowers rapid and accurate synthesis from Matlab models to create near ASIC like efficient solution. this platform, called SiLago (Silicon Lego) is benchmarked against a GPU implementation. the SiLago mentation of BioSOMs in four different dimensions, 128, 256, 512 and 1024 Neurons, were trained for two E Coli strains of bacteria with 40K training vectors. the results of SiLago implementation were benchmarked against a GPU GTX 1070 implementation in the CUDA framework. the comparison reveals 4 to 140x speed up and 4 to 5 orders of improvement in energy-delay product compared to implementation on GPU. this extreme efficiency comes with the added benefit of automated generation of GDSII level design from Matlab by using the Synchoros VLSI design style.

关键词： Neural networks Self-Organizing Maps SiLago Synchoros VLSI Design parallel architecture 3D DRAM GPU

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