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Exploring FPGAs for accelerating the phylogenetic likelihood function

Exploring FPGAs for accelerating the phylogenetic likelihood...

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International symposium on Parallel and Distributed Processing (IPDPS)

作者： N. Alachiotis E. Sotiriades A. Dollas A. Stamatakis Department of Electronic and Computer Engineering Technical University of Crete Crete Greece The Exelixis Laboratory Department of Computer Science Technische Universität München Munich Germany

Driven by novel biological wet lab techniques such as pyrosequencing there has been an unprecedented molecular data explosion. the growth of biological sequence data has significantly out-paced Moore's law. this development also poses new computational and architectural challenges for the field of phylogenetic inference, i.e., the reconstruction of evolutionary histories (trees) for a set of organisms which are represented by respective molecular sequences. Phylogenetic trees are currently increasingly reconstructed from multiple genes or even whole genomes. the introduced term "phylogenomics" reflects this development. Hence, there is an urgent need to deploy and develop new techniques and computational solutions to calculate the computationally intensive scoring functions for phylogenetic trees. In this paper, we propose a dedicated computer architecture to compute the phylogenetic maximum likelihood (ML) function. the ML criterion represents one of the most accurate statistical models for phylogenetic inference and accounts for 85% to 95% of total execution time in all state-of-the-art ML-based phylogenetic inference programs. We present the implementation of our architecture on an FPGA (field programmable gate array) and compare the performance to an efficient C implementation of the ML function on a high-end multi-core architecture with 16 cores. Our results are two-fold: (i) the initial exploratory implementation of the ML function for trees comprising 4 up to 512 sequences on an FPGA yields speedups of a factor 8.3 on average compared to execution on a single-core and is faster than the OpenMP-based parallel implementation on up to 16 cores in all but one case; and (ii) we are able to show that current FPGAs are capable to efficiently execute floating point intensive computational kernels.

关键词： Field programmable gate arrays Acceleration Phylogeny computer architecture Explosions Moore's Law Biology computing History Organisms Genomics

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Artificial intelligence model for transformer fault diagnosis using a constructed database

Artificial intelligence model for transformer fault diagnosi...

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the 16th IET International Conference on AC and DC Power Transmission (ACDC 2020)

作者： L. Wang T. Littler X. Liu Queen’s University Belfast School of Electronics Electrical Engineering and Computer Science Belfast UK

high capital investment in critical assets, in particular power transformers requires application of incisive diagnostics to determine performance and identify potential issues which may impact long-term operation and maintenance. Asset failure and replacement represent a worst-case scenario which can be avoided. this paper proposes a model for accurate transformer fault diagnosis using artificial intelligence (AI) methods. In recent years, AI models have evolved for fault classification using Dissolved Gas Analysis (DGA) data. In common practice, most DGA data are collated but less often labelled, thus restricting the development of diagnostic models with different learning approaches. To overcome this and related limitations, this paper proposes a new hybrid DGA method for unlabelled data to extract information to build a diagnostic database. the method uses the Rogers Ratio and Duval Triangle Methods to identify early and premature fault onset. the method also supports common utility asset practices to reduce transformer management costs by minimising damage from unnecessary invasive maintenance. the paper provides a comparative study of artificial neural network (ANN), support vector machine (SVM), K-Nearest Neighbour (KNN) and decision tree models using the constructed database. Comparative results indicate a high level of diagnostic precision with approximately 99% accuracy for classification using a KNN-based model.

关键词： power engineering computing fault diagnosis power transformers artificial intelligence power system faults pattern classification data analysis database management systems

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Parallel fuzzy inference system for large volumes of remote sensing data

Parallel fuzzy inference system for large volumes of remote ...

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IEEE International symposium on Industrial Electronics (ISIE)

作者： Sang Gu Lee Department of Computer Engineering Hannam University South Korea

ISBN: (纸本)0780370902

In the pattern recognition on the large volume of satellite images, the inference time is much increased. In the remote sensing data having 4 wavebands, 778 training patterns are learned. Each land cover pattern is classified by using 159900 patterns including trained patterns. In the fuzzy classification, 778 fuzzy rules are generated. Each fuzzy rule has 4 fuzzy variables in the condition part. therefore, high performance parallel fuzzy inference architecture is needed. In this paper, we propose a novel parallel fuzzy inference system on a T3E parallel computer. In this, fuzzy rules are distributed and executed simultaneously. the ONE-To-ALL algorithm is used to broadcast the fuzzy input to the all nodes. the results of the MIN/MAX operations are transferred to the output processor by the ALL-TO-ONE algorithm. By parallel processing of the fuzzy rules, the parallel fuzzy inference algorithm extracts match parallelism and achieves a good speed factor. this system can be used in a large expert system that has many inference variables in the condition and the consequent part.

关键词： Fuzzy systems Remote sensing Fuzzy control computer architecture Concurrent computing Parallel processing Control systems Inference algorithms Expert systems Database systems

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Energy efficiency and performance modeling of stencil applications on manycore and GPU computing resources

Energy efficiency and performance modeling of stencil applic...

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IEEE/ACM International symposium on Cluster computing and the Grid (CCGRID)

作者： Krzysztof Kurowski Miłosz Ciżnicki Jan Węglarz Poznań Supercomputing and Networking Center affiliated to IBCH PAS Poznań Poland Poznań University of Technology Poznań Poland

ISBN: (数字)9781728160955

One of the most critical application areas for many operational high-performance computing systems worldwide is a numerical weather prediction. Such complex predictions and corresponding computing models have to solve a large number of Partial Differential Equations using stencil computations on structured grids within tight production schedules. A stencil kernel within simulations is often the most demanding computing part and naturally may impact the energy consumption of the whole HPC system. In this paper, we introduce new functional extensions developed for DCworms and GSSIM simulators to predict the energy efficiency of extreme-scale stencil applications on heterogeneous computing resources, in particular consisting of a large number of many-core and GPUs. New energy-efficiency metrics for modeling of heterogeneous computing resources have been successfully added to the simulators thanks to their pluggable and extensible architectures. Our recent improvements related to application-specific performance models in simulators help users to take into account many relevant application parameters, in particular, those related to detailed energy consumption on heterogeneous HPC resources. We show in this paper how to extract stencil application-specific parameters based on real experiments. Moreover, we demonstrate how those parameters can be applied for modeling and simulation experiments to evaluate the overall performance and energy consumption of stencil computations on manycore CPUs and GPUs. Finally, we discuss new DCworms simulator capabilities and demonstrate added-values of performance analysis tools.

关键词： Computational modeling computer architecture Hardware Graphics processing units Energy consumption Predictive models

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Distributed acceleration of mobile radio network optimisation algorithms

Distributed acceleration of mobile radio network optimisatio...

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Wireless Telecommunications symposium, WTS

作者： Yuanzhou Ye Graham Megson School of Systems Engineering University of Reading Reading UK School of Electronics and Computer Science University of Westminster London UK

the past decade has witnessed explosive growth of mobile subscribers and services. With the purpose of providing better-swifter-cheaper services, radio network optimisation plays a crucial role but faces enormous challenges. the concept of Dynamic Network Optimisation (DNO), therefore, has been introduced to optimally and continuously adjust network configurations, in response to changes in network conditions and traffic. However, the realization of DNO has been seriously hindered by the bottleneck of optimisation speed performance. An advanced distributed parallel solution is presented in this paper, as to bridge the gap by accelerating the sophisticated proprietary network optimisation algorithm, while maintaining the optimisation quality and numerical consistency. the ariesoACP product from Arieso Ltd serves as the main platform for acceleration. this solution has been prototyped, implemented and tested. Real-project based results exhibit a high scalability and substantial acceleration at an average speed-up of 2.5, 4.9 and 6.1 on a distributed 5-core, 9-core and 16-core system, respectively. this significantly outperforms other parallel solutions such as multi-threading. Furthermore, augmented optimisation outcome, alongside high correctness and self-consistency, have also been fulfilled. Overall, this is a breakthrough towards the realization of DNO.

关键词： Acceleration Land mobile radio Telecommunication traffic Parallel processing Radio network Prototypes Testing Distributed computing computer architecture Concurrent computing

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Power and thermal Modeling of In-3D-Memory computing

Power and Thermal Modeling of In-3D-Memory Computing

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International symposium on Devices, Circuits and Systems (ISDCS)

作者： Jun-Han Han Robert E. West Karina Torres-Castro Nathan Swami Samira Khan Mircea Stan University of Virginia Charlottesville USA

ISBN: (数字)9781665414784

ISBN: (纸本)9781665447508

In-memory computing is an efficient big-data processing method that allows for performance scalability. Although 3D-memory is an established technology to integrate in-memory computing due to the 3D-stacked logic and memory layers, there are thermal issues and power budgets that restrict the integration of this concept in a 3D-stacked memory. In this paper, we investigate the power and thermal behavior of the in-3D-memory computing device based on thermal circuit modeling. When the logic layers consume 1 W/cm 2 in each layer, the maximum power available in the logic layer is 11.4 W/cm 2 and 7.3 W/cm 2 for the 4 and 16-layer stack. For high-rise stacked memory, passive heat sinks cannot sustain the operating temperature below 85 C. In this work, the validity of the proposed simulation results is compared with a conventional simulator.

关键词： Heating systems Computational modeling computer architecture Parallel processing Integrated circuit modeling Microfluidics Load modeling

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Large Scale Satellite Imagery Simulations with Physically Based Ray Tracing on Tianhe-1A Supercomputer

Large Scale Satellite Imagery Simulations with Physically Ba...

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IEEE International Conference on high performance computing and Communications (HPCC)

作者： Changmao Wu Yunquan Zhang Congli Yang University of Chinese Academy of Sciences Beijing China State Key Laboratory of Computer Architecture CAS Institute of Software CAS

Developing highly scalable algorithms for satellite imagery simulations is becoming increasingly important as scientists inquire to understand the mechanism of satellite imagery before satellites are launched into orbit. Although physically based ray tracing technique for image rendering has produced some of the most realistic images to date, studies on satellite imagery simulations using this technique are still very less to be seen, due in large part to both the complex physical processes and the computational difficulties of the mathematical models. In this paper, we present a highly scalable physically based ray tracer for satellite imagery simulations. Our ray tracer is based on a Master-Worker-Receiver framework which can overcome the performance bottleneck of Master node. Besides, a novel sample distribution strategy is presented by the authors, aiming at removing high additional computation overhead which is introduced by the currently available pixel distribution strategy. Compared to the pixel distribution strategy, our sample distribution strategy drops the computation overhead by 0.25 to 4 times. We also discuss the issue with granularity of assignment partitioning for Inter-Nodes and Intra-Nodes, then a hybrid scheduling strategy combining static and dynamic scheduling strategies is presented. Experiments show that our physically based ray tracer almost reaches to a linear speedup by using 16,800 CPU cores on Tianhe-1A Supercomputer. Our ray tracer is more efficient and highly scalable.

关键词： Ray tracing Satellites Receivers Distribution strategy Rendering (computer graphics) Load management Computational modeling

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On improving performance and energy profiles of sparse scientific applications 06

On improving performance and energy profiles of sparse scien...

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International symposium on Parallel and Distributed Processing (IPDPS)

作者： K. Malkowski Ingyu Lee P. Raghavan M.J. Irwin Department of Computer Science and Engineering Pennsylvania State University University Park PA USA

ISBN: (纸本)9781424400546

In many scientific applications, the majority of the execution time is spent within a few basic sparse kernels such as sparse matrix vector multiplication (SMV). Such sparse kernels can utilize only a fraction of the available processing speed because of their relatively large number of data accesses per floating point operation, and limited data locality and data re-use. Algorithmic changes and tuning of codes through blocking and loop unrolling schemes can improve performance but such tuned versions are typically not available in benchmark suites such as the SPEC CFP 2000. In this paper, we consider sparse SMV kernels with different levels of tuning that are representative of this application space. We emulate certain memory subsystem optimizations using SimpleScalar and Wattch to evaluate improvements in performance and energy metrics. We also characterize how such an evaluation can be affected by the interplay between code tuning and memory subsystem optimizations. Our results indicate that the optimizations reduce execution time by over 40%, and the energy by over 85%, when used with power control modes of CPUs and caches. Furthermore, the relative impact of the same set of memory subsystem optimizations can vary significantly depending on the level of code tuning. Consequently, it may be appropriate to augment traditional benchmarks by tuned kernels typical of high performance sparse scientific codes to enable comprehensive evaluations of future systems.

关键词： Kernel Sparse matrices Application software computer architecture Computational modeling Power control Scientific computing Microprocessors computer science Power engineering and energy

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Ultrasound therapy system and ablation results utilizing miniature imaging/therapy arrays

Ultrasound therapy system and ablation results utilizing min...

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IEEE symposium (IUS) Ultrasonics

作者： P.G. Barthe M.H. Slayton P.M. Jaeger I.R.S. Makin L.A. Gallagher T.D. Mast M.M. Runk W. Faid Guided Therapy Systems Mesa AZ USA Ethicon Endo-Surgery Cincinnati OH USA

Array-based imaging and therapy systems have several advantages over single element approaches, and it was previously shown that the imaging and therapy functionality may be combined into dual-mode arrays. In this work, minimally invasive, miniature (2.2 mm /spl times/ 50 mm aperture, 3.3 mm diameter) dual-mode linear arrays have been developed into probes with high acoustic power output (100 W, and >120 W/cm/sup 2/ at the source), high transmit efficiency (>65% typical), and good imaging performance (3.4 MHz center frequency, 50% fractional bandwidth, >100 mm deep field of view). these therapy / imaging probes have been integrated into a flexible intense ultrasound surgery platform which also includes conventional diagnostic imaging probes. A system architecture has been developed which includes a 64-channel therapy driver with software selection of array aperture and phasing (1/16th wavelength), frequency (0.5-8 MHz), drive amplitude (5 W/channel, nominal), mechanical rotational steering (/spl plusmn/180 degrees), and temporal sequencing/switching of imaging, and therapy modes. the array-based imaging/therapy system has produced encouraging results in preclinical studies of bulk tissue ablation, imaging and treatment monitoring of liver in vitro and in vivo, examples of which are presented. the system can be applied to ablation of other soft tissue pathologies, e.g. kidney, heart, uterus, brain, GI, etc.

关键词： Ultrasonic imaging Medical treatment Acoustic imaging Probes Apertures Frequency Minimally invasive surgery Acoustic arrays Bandwidth computer architecture

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GLOBAL DETERMINISTIC AND STOCHASTIC OPTIMIZATION IN A SERVICE ORIENTED architecture 17

GLOBAL DETERMINISTIC AND STOCHASTIC OPTIMIZATION IN A SERVIC...

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Simulation Multiconference

作者： Chaitra Raghunath Tyler H. Chang Mohamed Jrad Rakesh K. Kapania Layne T. Watson Raymond M. Kolonay Dept. of Computer Science Virginia Polytechnic Institute & State University Dept. of Aerospace & Ocean Eng. Virginia Polytechnic Institute & State University Dept. of Computer Science Dept. of Mathematics Dept. of Aerospace & Ocean Eng. Virginia Polytechnic Institute & State University AFRL/RQVC

ISBN: (纸本)9781510838222

Service ORiented computing EnviRonment (SORCER) is a Java-based network-centric computing platform. SORCER provides a service oriented architecture, which enables the implementation of parallel algorithms in a dynamic distributed computing environment. SORCER is often used for multidisciplinary aircraft design analysis and optimization. However, the current approach often assigns intense optimization algorithms to run entirely on single overloaded nodes, rather than evenly distributing the workload. the goal of this work is to provide lower-level optimization algorithms as integrated SORCER services and study the overhead of doing so. VTDIRECT95, a Fortran 95 implementation of D. R. Jones' algorithm DIRECT, is a highly parallelizable derivative-free deterministic global optimization algorithm. QNSTOP is a parallel quasi-Newton algorithm for stochastic optimization problems. the potential benefit of integrating VTDIRECT95 and QNSTOP into the SORCER framework is to provide dynamic load balancing among computational resources at the optimization level, resulting in a dynamically scalable process.

关键词： Service-oriented computing Deterministic global optimization Stochastic optimization Multi-disciplinary design architecture Legal Services Optimization algorithms Service-oriented architecture Building construction Parallel algorithms network-centric computing multidisciplinary information Load balancing QNA

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