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high-performance homomorphic matrix completion on GPUs 21

High-performance homomorphic matrix completion on GPUs

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21st IEEE international Conference on high performance computing and Communications, 17th IEEE international Conference on Smart City and 5th IEEE international Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Lu, Han Zhang, Tao Liu, Xiao-Yang School of Computer Engineering and Science Shanghai University China Department of Electrical Engineering Columbia University United States Shanghai Institute for Advanced Communication and Data Science China

ISBN: (纸本)9781728120584

Data loss and privacy exposure are two major issues in many applications such as trajectory tracking and online recommendations. The homomorphic matrix completion (HMC) is a promising approach to address these two issues simultaneously and to exploit the computing power of cloud servers. However, HMC comprises a compute-intensive matrix completion procedure, making it impractical for a cloud server to host large-scale parallel requests in real-time. In this paper, we propose a high-performance homomorphic matrix completion approach by offloading the matrix completion task from CPUs to commodity GPUs (Graphics Processing Units) widely installed in cloud servers. We propose optimization strategies for efficient memory access, reduced memory consumption, and batched least squares (LS) minimization to improve performance. Experiment results with similar recovery errors on both CPUs and GPUs demonstrate the homomorphism property for the matrix completion task. For small-or medium-scale matrices of various sizes, the proposed approach achieves an average of 66.84X and up to 116.23X speedups over dual 10-core Xeon CPUs. We further propose a method for computing large-scale matrices exceeding the GPU memory capacity and it achieves an average of 71.85X and up to 174.92X speedups versus dual 10-core Xeon CPUs. © 2019 IEEE.

关键词： Graphics processing unit

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A fault-tolerant routing strategy with graceful performance degradation for fat-tree topology supercomputer 21

A fault-tolerant routing strategy with graceful performance ...

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作者： Xu, Jiaqing Cai, Dongjing He, Jie Tang, Fuqiao School of Computer National University of Defense Technology Changsha Hunan China

ISBN: (纸本)9781728120584

In recent years, in order to solve the problem of high-speed signal transmission quality, the solution of short reach HSS + on-board optics + passive optical fiber is gradually replacing the original long reach HSS + AOC inter-switch interconnection scheme. When the on-board optics fails, its replacement time will be much higher than that of AOC, which increases the duration of interconnection failure in the system. We believe that it is essential that the fault-tolerant routing strategy can reduce the degradation of the performance of the interconnection network without suspending the operation of the tasks, as this will greatly improve the overall availability of the system during the duration of the failure. In this paper, a fault-tolerant routing strategy for fat-tree topology is proposed, which can tolerate multiple interconnect failures with only a graceful performance degradation through actual system testing. © 2019 IEEE.

关键词： Fault tolerance

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Analyzing and predicting the popularity of online content using the weak ties theory 21

Analyzing and predicting the popularity of online content us...

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作者： Wang, Xiaomeng Fang, Binxing Zhang, Hongli Wang, Xing School of Computer Science and Technology Harbin Institute of Technoloay Harbin China

ISBN: (纸本)9781728120584

With the rapid development of online social networks (OSNs), a huge amount of user generated online content is gradually affecting people's lives. Popularity prediction of online content aims to predict the popularity in the future based on its early diffusion status. Existing models for popularity prediction are mostly based on discovering network features or fitting the equation into a varying time function which seldom make full use of the law of sociology. The main contribution of this article is to solve the problem that the accuracy of current popularity prediction model is not high enough and few or no work based on sociology. In this paper, we find that there exists a high linear correlation between the proportion of faithful fans in Facebook homepage with frequent shares in the early and the future popularity. The statistical results about Facebook remind us that the weak ties theory plays an important role in prediction task. Furthermore, an experimental study clearly illustrates that the effectiveness of the proposed method. © 2019 IEEE.

关键词： Social networking (online)

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Large-scale lattice boltzmann method simulations of stenosed carotid bifurcation 21

Large-scale lattice boltzmann method simulations of stenosed...

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作者： Ge, Sen Xie, Jiang Wang, Haiya Zhu, Cong Zhang, Wu School of Computer Engineering and Science Shanghai University Shanghai China Geriatric Department Shanghai Jiaotong University School of Medicine Affiliated Renji Hospital Shanghai China Materials Genome Institute of Shanghai University Shanghai University Shanghai China Shanghai Institute of Applied Mathematics and Mechanics Shanghai University Shanghai China

ISBN: (纸本)9781728120584

Carotid artery diseases are extremely harmful to the human brain, especially unstable plaques. Wall shear stress is significant for clinical diagnosis of carotid plaque stability. The challenge of the traditional simulation method is that preprocessing time and computation time of large-scale simulation are relatively long. In this paper, a fast simulation procedure for two-dimensional (2D) and three-dimensional (3D) blood flow models of stenosed carotid based on parallel lattice Boltzmann method was proposed. The geometry model of carotid artery stenosis was established by medical image reconstruction method. For computational grid generation, in the 3D model, we used the wall encryption grid method to improve the precision of the near wall blood flow simulation and reduce the number of computational grids. The simulation results were compared with the analytic results to verify the rationality and accuracy of the model. In order to meet the clinical requirements, especially the limited diagnostic time, parallel optimization was carried out in high performance computing cluster. The simulation results show that the parallel algorithm with OpenMP libraries were more than 15 times faster than the serial simulations. Our method can assist doctors to diagnose carotid artery disease in a short time. © 2019 IEEE.

关键词： Diagnosis

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Efficient wear leveling for PCM/dram-based hybrid memory 21

Efficient wear leveling for PCM/dram-based hybrid memory

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作者： Liu, Ruicheng Jin, Peiquan Wu, Zhangling Wang, Xiaoliang Wan, Shouhong Hua, Bei School of Computer Science and Technology University of Science and Technology of China Hefei230026 China Key Lab. of Electromagnetic Space Information Chinese Academy of Sciences Hefei230026 China

ISBN: (纸本)9781728120584

Phase change memory (PCM) has emerged as a promising candidate for next-generation storage media, owing to its low power consumption, non-volatility, and high scalability. However, PCM has limited write endurance, or more particularly, it can only undergo a limited number of wearing operations. This problem is much critical to the lifetime of PCM. Aiming to solve this problem, in this paper we propose an efficient wear leveling design for PCM/DRAM-based hybrid memory systems, which is able to balance the write operations to PCM and lengthen the lifetime of PCM. In particular, we first propose a new architecture called MH-BS (MinHeap Buddy System) for PCM/DRAM-based hybrid memory, in which DRAM and PCM are both employed as main memory. Next, we propose two new structures to management the spaces of PCM, namely a minimum heap array (MinHeap-Array) and a wear-skewed array (WearSkew-Array). We devise efficient algorithms for memory allocation and reclaim based on the proposed structures. With these mechanisms, write operations are distributed to PCM chips in a balanced manner and the write amplification ratio of PCM incurred by page swaps is reduced, yielding a better wear leveling for PCM and longer lifetime of PCM. Our experimental results on a simulated PCM/DRAM-based hybrid memory system and four kinds of workloads show that our proposal is efficient for the wear leveling of PCM, and thus offers a more practical solution for the memory management on PCM/DRAM-based hybrid memory systems. © 2019 IEEE.

关键词： Phase change memory

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RadixKV: A memory efficient and high performance key-value store 21

RadixKV: A memory efficient and high performance key-value s...

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作者： Zhang, Zhou Jin, Peiquan Hao, Xingjun Liu, Ruicheng Wang, Xiaoliang Wan, Shouhong School of Computer Science and Technology University of Science and Technology of China Hefei230026 China Key Lab. of Electromagnetic Space Information Chinese Academy of Sciences Hefei230026 China

ISBN: (纸本)9781728120584

With the rapid development of the Internet of things (IoT), massive sensing data are continuously sent to data centers. Big sensing data call for efficient approaches on data storage and retrieval, because many IoT applications need real-time query performance. The Radix Tree is an efficient tree structure that has constant query time complexity which is much suitable for real-time query processing. However, it has high space cost and index building time, which will worsen the overall performance especially in update-intensive scenarios. In this paper, we propose a memory-efficient high-performance key-value system called RadixKV, which offers efficient improvements on the Radix Tree. We first analyze the online update performance of the Radix Tree and design an adaptive parallel index update strategy. Then, we propose Radix Array, which is a space optimized data structure for the Radix Tree. We conduct comparative experiments to evaluate the performance of RadixKV and compare RadixKV with previous works including Adaptive Radix Tree and Pre-order Radix Tree. The results show that RadixKV reduces 92.7% and 32.2% of space costs respectively, compared with the Adaptive Radix Tree and the Pre-order Radix Tree. In addition, RadixKV achieves the best write performance and has low index building time as well as query latency. © 2019 IEEE.

关键词： Internet of things

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Accelerating HPC applications using computational storage devices 21

Accelerating HPC applications using computational storage de...

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作者： Torabzadehkashi, Mahdi Heydarigorji, Ali Rezaei, Siavash Bobarshad, Hosein Alves, Vladimir Bagherzadeh, Nader Samueli School of Engineering University of California Irvine NGD Systems Inc. IrvineCA United States Computer Science Department University of California Irvine NGD Systems Inc. IrvineCA United States NGD Systems Inc. IrvineCA United States

ISBN: (纸本)9781728120584

During the past decades, computers have become more powerful, and the size of the problems they can solve have increased drastically. Today's supercomputers have millions of processors orchestrated together to create an environment for solving superscale problems. On the other hand, the power consumption of modern supercomputers has increased to thousands of kWs and data movements account for a large portion of this increment. In this paper, we show how computational storage technology -running applications inside storage devices-provides a scalable solution for running HPC applications and improves performance while decreasing energy consumption. We introduce Catalina, a high-capacity Computational storage Device (CSD) that is capable of running a wide range of applications in-place by utilizing a quad-core 64-bit ARM processor coupled with NEON SIMD engines. As the proof of concept, we built a fully-functional Catalina prototype and a server including six Catalina CSDs to run HPC applications. The results show up to 2.2x improvement in performance and 54% reduction in energy consumption for running multi-dimensional FFT benchmarks on different datasets. © 2019 IEEE.

关键词： Fast Fourier transforms

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PDMF: Parallel dictionary motif finder on multicore and GPU 21

PDMF: Parallel dictionary motif finder on multicore and GPU

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作者： Salomon, Michelle Soundarajan, Sanjay Park, Jin H. Computer Science Department California State University Fresno FresnoCA United States

ISBN: (纸本)9781728120584

Unknown motif finding in a set of DNA sequences is an important step of understanding the functionality of a group of genes and it requires accuracy and efficiency. We propose and present high-performance computation models for accelerating an efficient combinatorial approach of finding motif, which uses tree based bypassing and hash based heuristics to skip unnecessary computations with keeping the maximum accuracy. The computation models are designed for multicore processors and GPU and implemented with OpenMP and CUDA, respectively. To achieve the maximum efficiency, we also developed efficient heterogeneous computation models, in which multicore processor(s) and GPU collaborate. The collection of the resulting products is named PDMF and tested on a couple of HPC systems for performance. Our experimental results showed that the multicore version (PDMFm) achieved average 4.63x and 8.87x speedups over the serial version on a couple of systems with 4 cores and 16 cores, respectively. The GPU version (PDMFg) achieved average 41.48x and 9.95x speedups over the serial version and PDMFm on a system with a 4-core host CPU and a GPU. The best heterogeneous version showed ~1.4x speedup over the baseline GPU version. © 2019 IEEE.

关键词： Graphics processing unit

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Interference-Aware I/O scheduling for data-intensive applications on hierarchical HPC storage systems 21

Interference-Aware I/O scheduling for data-intensive applica...

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作者： Liang, Weihao Chen, Yong An, Hong School of Computer Science and Technology University of Science and Technology of China Hefei China Department of Computer Science Texas Tech University LubbockTX United States

ISBN: (纸本)9781728120584

Scientific applications in critical areas are becoming more and more data-intensive. As data volume continues to grow, the data movement from memory to storage system has turned into a crucial performance bottleneck for many data-intensive applications. Newly emerged burst buffer concept provides a promising solution by increasing the depth of storage hierarchy to increase I/O performance of data-intensive applications. However, the data management on such multi-layer hierarchical storage system is still understudied. How to leverage each layer of storage for efficient data movement is an important research topic for HPC field. In this paper, we present a dynamic, interference-aware scheduling scheme that can efficiently manages the I/O scheduling among different layers of hierarchical HPC storage system to coordinate multiple concurrent data-intensive applications. Extensive experiments have been conducted and the results have demonstrated that our proposed approach can significantly improve the I/O performance of data-intensive applications. © 2019 IEEE.

关键词： Scheduling

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Real-time trajectory similarity processing using longest common subsequence 21

Real-time trajectory similarity processing using longest com...

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作者： Ding, Jiafeng Fang, Junhua Zhang, Zonglei Zhao, Pengpeng Xu, Jiajie Zhao, Lei School of Computer Science Technology Soochow University Suzhou China

ISBN: (纸本)9781728120584

Driven by the fast development of mobile internet and mobile devices, huge volumes of trajectory data describing the spatial-temporal information of moving objects are currently generated. Trajectory similarity processing is playing a critical role to explore valuable information, such as the patterns of human activities and behaviors. However, most of the existing works optimize this operation in an off-line manner, which is unable to provide timely feedback for time-sensitive applications. In this paper, we present a new real-time processing framework for trajectory similarity measurement, with practical algorithms to reduce the computing resource cost and guarantee the correctness of the result. Our proposal includes a cost-effective framework to ensure the correctness of trajectory similarity processing, a stream partition algorithm to maximize the processing throughput, a lightweight Top-k computing mode to cut off unnecessary network cost. Empirical studies on real-world stream applications validate the usefulness of our proposals and prove the huge advantage of our approaches over state-of-the-art solutions in the literature. © 2019 IEEE.

关键词： Cost effectiveness

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