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Selective Caching: Avoiding Performance Valleys in Massively parallel Architectures

Selective Caching: Avoiding Performance Valleys in Massively...

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euromicro conference on parallel, distributed and network-based processing

作者： Amin Jadidi Mahmut T. Kandemir Chita R. Das Cadence Design Systems Department of Computer Science and Engineering Pennsylvania State University USA

ISBN: (数字)9781728165820

ISBN: (纸本)9781728165837

Emerging general purpose graphics processing units (GPGPU) make use of a memory hierarchy very similar to that of modern multi-core processors - they typically have multiple levels of on-chip caches and a DDR-like off-chip main memory. In such massively parallel architectures, caches are expected to reduce the average data access latency by reducing the number of off-chip memory accesses; however, our extensive experimental studies confirm that not all applications utilize the on-chip caches in an efficient manner. Even though GPGPUs are adopted to run a wide range of general purpose applications, the conventional cache management policies are incapable of achieving the optimal performance over different memory characteristics of the applications. this paper first investigates the underlying reasons for inefficiency of common cache management policies in GPGPUs. To address and resolve those issues, we then propose (i) a characterization mechanism to analyze each kernel at runtime and, (ii) a selective caching policy to manage the flow of cache accesses. Evaluation results of the studied platform show that our proposed dynamically reconfigurable cache hierarchy improves the system performance by up to 105% (average of 27%) over a wide range of modern GPGPU applications, which is within 10% of the optimal improvement.

关键词： Kernel Instruction sets Graphics processing units System performance System-on-chip parallel processing Delays

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Adaptive Load Balancing based on Machine Learning for Iterative parallel Applications

Adaptive Load Balancing based on Machine Learning for Iterat...

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euromicro conference on parallel, distributed and network-based processing

作者： C. R. Anna Victoria Oikawa Vinicius Freitas Márcio Castro Laércio L. Pilla Federal University of Santa Catarina (UFSC) Florianopolis Brazil LRI Univ. Paris-Saclay – CNRS Orsay France

ISBN: (数字)9781728165820

ISBN: (纸本)9781728165837

the performance of irregular scientific applications can be easily affected by an uneven distribution of work among the computing resources. In this context, Load Balancing (LB) stands as one of the most important solutions to improve resource utilization. However, choosing the best-performing load balancing algorithm for a given application is not a trivial task. For instance, manually and statically choosing an LB algorithm does not work in situations where applications have a dynamic or unknown behavior. In this context, we propose a Machine Learning-based Adaptive Load Balancer (ADAPTIVELB) to automate the load balancing algorithm decision at run time. this approach monitors and collects information about the application dynamically, and according to the analyzed data, it makes a decision of invoking the most suitable LB algorithm. Our experiments show that ADAPTIVELB can select a good load balancing algorithm in most of the cases, leading to performance improvements over statically chosen LB algorithms and over the absence of a load balancer.

关键词： Task analysis Heuristic algorithms Load management Machine learning algorithms Adaptation models Prediction algorithms Machine learning

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XKBlas: a High Performance Implementation of BLAS-3 Kernels on Multi-GPU Server

XKBlas: a High Performance Implementation of BLAS-3 Kernels ...

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euromicro conference on parallel, distributed and network-based processing

作者： thierry Gautier João V. F. Lima LIP Laboratory INRIA CNRS UCL-Lyon France Graduate Program in Computer Science Universidade Federal de Santa Maria – Santa Maria Brazil

ISBN: (数字)9781728165820

ISBN: (纸本)9781728165837

In the last ten years, GPUs have dominated the market considering the computing/power metric and numerous research works have provided Basic Linear Algebra Subprograms implementations accelerated on GPUs. Several software libraries have been developed for exploiting performance of systems with accelerators, but the real performance may be far from the platform peak performance. this paper presents XKBlas that aims to improve performance of BLAS-3 kernels on multi-GPU systems. At low level, we model computation as a set of tasks accessing data on different resources. At high level, the API design favors non-blocking calls as uniform concept to overlap latency, even by fine grain computation. Unit benchmark of BLAS-3 kernels showed that XKBlas outperformed most implementations including the overhead of dynamic task's creation and scheduling. XKBlas outperformed BLAS implementations such as cuBLAS-XT, PaRSEC, BLASX and Chameleon/StarPU.

关键词： Task analysis Graphics processing units Libraries Kernel Layout Runtime Matrix decomposition

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Evaluating the performance and improving the usability of parallel and distributed Word Embeddings tools

Evaluating the performance and improving the usability of pa...

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euromicro conference on parallel, distributed and network-based processing

作者： Matheus L. da Silva Vinícius Meyer Dionatrã F. Kirchoff F. S. Joaquim Neto Renata Vieira A. F. César De Rose Polytechnic School Pontifical Catholic University of Rio Grande do Sul (PUCRS) Porto Alegre RS Brazil

ISBN: (数字)9781728165820

ISBN: (纸本)9781728165837

the representation of words by means of vectors, also called Word Embeddings (WE), has been receiving great attention from the Natural Language processing (NLP) field. WE models are able to express syntactic and semantic similarities, as well as relationships and contexts of words within a given corpus. Although the most popular implementations of WE algorithms present low scalability, there are new approaches that apply High-Performance Computing (HPC) techniques. this is an opportunity for an analysis of the main differences among the existing implementations, based on performance and scalability metrics. In this paper, we present a study which addresses resource utilization and performance aspects of known WE algorithms found in the literature. To improve scalability and usability we propose a wrapper library for local and remote execution environments that contains a set of optimizations such as the pWord2vec, pWord2vec MPI, Wang2vec and the original Word2vec algorithm. Utilizing these optimizations it is possible to achieve an average performance gain of 15x for multicores and 105x for multinodes compared to the original version. there is also a big reduction in the memory footprint compared to the most popular python versions.

关键词： Optimization Scalability Libraries Training Usability Natural language processing Computer architecture

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Efficient On-Chip Multicast Routing based on Dynamic Partition Merging

Efficient On-Chip Multicast Routing based on Dynamic Partiti...

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euromicro conference on parallel, distributed and network-based processing

作者： Binayak Tiwari Mei Yang Yingtao Jiang Xiaohang Wang Department of Electrical and Computer Engineering University of Nevada Las Vegas Las Vegas USA School of Software Engineering South China University of Technology Guangzhou China

ISBN: (数字)9781728165820

ISBN: (纸本)9781728165837

networks-on-chips (NoCs) have become the mainstream communication infrastructure for chip multiprocessors (CMPs) and many-core systems. the commonly used parallel applications and emerging machine learning-based applications involve a significant amount of collective communication patterns. In CMP applications, multicast is widely used in multithreaded programs and protocols for barrier/clock synchronization and cache coherence. Multicast routing plays an important role on the system performance of a CMP. Existing partition-based multicast routing algorithms all use static destination set partition strategy which lacks the global view of path optimization. In this paper, we propose an efficient Dynamic Partition Merging (DPM)-based multicast routing algorithm. the proposed algorithm divides the multicast destination set into partitions dynamically by comparing the routing cost of different partition merging options and selecting the merged partitions with lower cost. the simulation results of synthetic traffic and PARSEC benchmark applications confirm that the proposed algorithm outperforms the existing path-based routing algorithms. the proposed algorithm is able to improve up to 23% in average packet latency and 14% in power consumption against the existing multipath routing algorithm when tested in PARSEC benchmark workloads.

关键词： Routing Partitioning algorithms Heuristic algorithms Merging Unicast System recovery Protocols

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A GPU enhanced LIDAR Perception System for Autonomous Vehicles

A GPU enhanced LIDAR Perception System for Autonomous Vehicl...

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euromicro conference on parallel, distributed and network-based processing

作者： Abderrahim Haneche Yazid Lachachi Smail Niar Hamza Ouarnoughi Ecole Nationale Supérieure d’Informatique Algiers Algeria Université des sciences et de la technologie d’Oran Oran Algeria LAMIH/CNRS Université Polytechnique Hauts-de-France Valenciennes France

ISBN: (数字)9781728165820

ISBN: (纸本)9781728165837

Environment vision and understanding is a crucial task in Autonomous Driving (AD) context. this mainly needs image processing approaches such as Convolutional Neural networks (CNN). Nevertheless, cameras have shown their limits for such a task, especially in dealing with difficult light conditions. LIDAR is a powerful and widely used sensor for AD. Indeed, LIDAR can then cope with the lack of information gathered from cameras. For AD, data processing from the sensors is the key function to obtain a high quality perception. For this, Graphics processing Unit (GPU) platforms show great performances and outperform other processing platforms such as FPGA and Multi-cores. this work presents a new approach to produce multiple 2D representation from 3D points cloud coming from LIDAR. the 2D representation can therefore be used by any efficient image processing applications. Our approach uses only LIDAR sensor and exploits the high GPU parallelism for its implementation. the resulting 2D representations are then used by CNN for AD applications such as image classification and segmentation. Finally, our contributions have been evaluated using the KITTI road benchmark and showed encouraging results.

关键词： Laser radar Graphics processing units Two dimensional displays three-dimensional displays Task analysis Cameras Rendering (computer graphics)

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Off-Chip Congestion Management for GPU-based Non-Uniform processing-in-Memory networks

Off-Chip Congestion Management for GPU-based Non-Uniform Pro...

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euromicro conference on parallel, distributed and network-based processing

作者： Kishore Punniyamurthy Andreas Gerstlauer The University of Texas at Austin

ISBN: (数字)9781728165820

ISBN: (纸本)9781728165837

Advancements in packaging and 3D-stacking technology have enabled novel non-uniform processing-in-memory (NUPIM) architectures integrating a network of hybrid modules each with varying sizes and proportions of compute and memory. In such systems, network congestion can have a significant impact on performance and energy-efficiency scaling. At the same time, NUPIM systems often have strict power and thermal constraints, where traditional routing/redundancy or buffering based approaches to reduce congestion cannot be *** this paper, we propose a low-overhead yet scalable scheme for congestion management in off-chip networks of emerging GPU-based NUPIM systems. We note that congestion in NUPIM networks exhibits a form of tree saturation in which individually congested links form congested paths, where congestion effects due to back pressure vary across paths. Additionally, memory responses can have different performance impact due to memory divergence. Our approach exploits differences in performance impact of NUPIM traffic to mitigate congestion effects. We dynamically track congested paths and divergent data to manage priorities and accelerate performance-critical traffic. We further use critical paths knowledge to dynamically manage link widths and save I/O *** show that our congestion management outperforms a configuration with double the number of virtual channels and buffers indicating its effectiveness in managing congestion under stringent constraints. It improves performance by 15% (and up to 31%) over baseline and 10% (and up to 29%) against a memory distance based approach for congestion-affected benchmarks. Our scheme reduces 78% of I/O energy on average and up to 29% of system energy across all benchmarks.

关键词： Benchmark testing Delays Market research Systems architecture Packaging Memory management

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Acceleration of Radiofrequency Ablation Process for Liver Cancer Using GPU

Acceleration of Radiofrequency Ablation Process for Liver Ca...

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euromicro conference on parallel, distributed and network-based processing

作者： Claudio Schepke Marcelo Cogo Miletto Laboratório de Estudos Avançados (LEA) Federal University of Pampa - UNIPAMPA Campus Alegrete Brazil Grupo de Processamento Paralelo e Distribuído - GPPD Federal University of Rio Grande do Sul - UFRGS Campus do Vale Brazil

ISBN: (数字)9781728165820

ISBN: (纸本)9781728165837

Computational simulation is a technique used in several research areas. In medicine, the Radiofrequency Ablation Finite Element Method (RAFEM) application was developed to simulate the RadioFrequency Ablation (RFA) process, which is a medical procedure to treat hepatic cancer. this application presents a high computational time to perform a simulation, taking up to 20 hours for simulation while the RFA procedure itself lasts from four to six minutes. Some efforts have already been carried out to obtain better performance for the application. However, none of them considered the use of GPUs, which is an architecture that can be used to accelerate finite element method applications. this work aims to propose a parallelization approach to explore ways to obtain better performance for the application through the use of GPUs to reduce the execution time under a few minutes. We adopted an iterative development process to coordinate and to generate parallel versions of the code. through this process allied to the use of GPU-accelerated code libraries, it was possible to create different versions of the application, adding improvements to each one. the results obtained with the best version showed a reduction of the computation time by up to 18 times. therefore, this improvement makes the use of RAFEM application more feasible in health treatment by reducing the waiting time for the results.

关键词： Finite element analysis Mathematical model Graphics processing units Liver Computational modeling Matrices Acceleration

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Proceedings - 2019 IEEE Intl Conf on parallel and distributed processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and networking, ISPA/BDCloud/SustainCom/SocialCom 2019

Proceedings - 2019 IEEE Intl Conf on Parallel and Distribute...

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17th IEEE International conference on parallel and distributed processing with Applications, 9th IEEE International conference on Big Data and Cloud Computing, 9th IEEE International conference on Sustainable Computing and Communications, 12th IEEE International conference on Social Computing and networking, ISPA/BDCloud/SustainCom/SocialCom 2019

ISBN: (纸本)9781728143286

the proceedings contain 232 papers. the topics discussed include: convolutional neural network-based approach for citrus diseases recognition;using temporal conceptual graphs and neural networks for big data-based attack scenarios reconstruction;taxi demand prediction with LSTM-based combination model;counting attention based on classification confidence for visual question answering;an optimization method of WebP images lossy compression algorithm for FPGAs;self-adaptive address mapping mechanism for access pattern awareness on DRAM;a high-performance self-learning antelopes migration algorithm (SAMA) for global optimization;and using resource use data and system logs for HPC system error propagation and recovery diagnosis.

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An Ethereum-based Energy Trading Protocol (EETP) 12

An Ethereum-based Energy Trading Protocol (EETP)

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12th International conference on Cyber-Enabled distributed Computing and Knowledge Discovery, CyberC 2020

作者： thibodeau Hafid, Yassin M. Makrakis, Dimitrios Elie, Etienne University of Ottawa Canada Intel California United States

ISBN: (纸本)9781728184487

Nowadays, the proportion of the global supply of green energy sources (e.g., solar and wind) is increasing dramatically. Integrating these sources into the current smart grid is very challenging, given that the smart grid has centralized topology which is costly and inefficient. In particular, the current procedures used in the wholesale energy market are slow, time-consuming and thus expensive for small-scale energy sources (e.g., small-scale solar energy farms). Indeed, these sources are excluded in practice from the energy market. thus, to integrate the increasing number of small-scale energy sources, there is a need to transform the smart grid into a decentralized system. A promising technology to realize this decentralization is Blockchain. With its characteristics like immutability, security, and decentralization, we believe that Blockchain will be the core technology for the future decentralized smart grid. In this paper, we propose a peer-To-peer (P2P) energy trading system based on Ethereum. the objective is to allow any participant (e.g., big/small producers and consumers) to securely trade energy with minimum cost. the proposed approach moves most of the processing and storage off-chain, with the objective to minimize the cost of on-chain (i.e., smart contract) processing and storage while guaranteeing the security of the trading process. Stable coins are used to pay for the trade so as to overcome the problem of the instability regarding cryptocurrency exchange rates. Our proposal has been implemented, tested and deployed on the Ethereum official test network Ropsten. the results show that the proposed approach implements the P2P trading process with very small cost, making it an affordable solution for all participants, including small-scale sources. © 2020 IEEE.

关键词： Smart contract

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