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2011 IEEE 2nd International Conference on Software Engineering and Service Science, ICSESS 2011

作者： Yun, Long Yang, Yan Wang, Jing Zhu, Ge Dept. of Computer Science and Technology Heilongjiang University Key Lab. of Database and Parallel Computing Heilongjiang Province Harbin China

ISBN: (纸本)9781424496969

Memory-based collaborative filtering algorithms have been widely adopted in many popular recommender systems, however the rating data are very sparse, which affects prediction accuracy greatly. To solve this problem, we use expert opinions to improve prediction accuracy. Firstly, we propose a novel similarity measure in order to highlight users' background. Then, combining users' ratings with expert opinions, the prediction get a right balance in both expert professional opinions and similar users. Finally, since SVD-based collaborative filtering algorithms shows good performance on the prevention of noise, we use it to smooth the prediction. Experiments of MovieLens have shown that our proposed method improves recommendation quality obviously. © 2011 IEEE.

关键词： Collaborative filtering

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Designing fast architecture-sensitive tree search on modern multicore/many-core processors

Designing fast architecture-sensitive tree search on modern ...

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作者： Kim, Changkyu Chhugani, Jatin Satish, Nadathur Sedlar, Eric Nguyen, Anthony D. Kaldewey, Tim Lee, Victor W. Brandt, Scott A. Dubey, Pradeep Intel Corporation Parallel Computing Lab United States Oracle Corporation United States University of California Santa Cruz United States

In-memory tree structured index search is a fundamental database operation. Modern processors provide tremendous computing power by integrating multiple cores, each with wide vector units. There has been much work to exploit modern processor architectures for database primitives like scan, sort, join, and aggregation. However, unlike other primitives, tree search presents significant challenges due to irregular and unpredictable data accesses in tree traversal. In this article, we present FAST, an extremely fast architecturesensitive layout of the index tree. FAST is a binary tree logically organized to optimize for architecture features like page size, cache line size, and Single Instruction Multiple Data (SIMD) width of the underlying hardware. FAST eliminates the impact of memory latency, and exploits thread-level and data-level parallelism on both CPUs and GPUs to achieve 50 million (CPU) and 85 million (GPU) queries per second forlarge trees of 64M elements, with even better results on smaller trees. These are 5X (CPU) and 1.7X (GPU) faster than the best previously reported performance on the same architectures. We also evaluated FAST on the Intel® Many Integrated Core architecture (IntelR MIC), showing a speedup of 2.4X-3X over CPU and 1.8X-4.4X over GPU. FAST supports efficient bulk updates by rebuilding index trees in less than 0.1 seconds for datasets as large as 64M keys and naturally integrates compression techniques, overcoming the memory bandwidth bottleneck and achieving a 6X performance improvement over uncompressed index search for large keys on CPUs. © 2011 ACM.

关键词： Graphics processing unit

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Unified Contextualized Knowledge Embedding Method for Static and Temporal Knowledge Graph

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IEEE/ACM Transactions on Audio Speech and Language Processing 2024年 33卷 82-95页

作者： Gao, Yifu Qiao, Linbo Huang, Zhen Kan, Zhigang He, Yongquan Li, Dongsheng National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing College of Computer Science and Technology Changsha410000 China Intelligent Game and Decision Lab Beijing China Meituan Beijing100102 China

Recent years, there is a growing interest in knowledge graph embedding (KGE), which maps symbolic entities and relations into low-dimensional vector space to effectively represent structured data from the knowledge graph. In addition, the concept of temporal knowledge graph is proposed to document dynamically changing facts in the real world. Existing works attempt to incorporate temporal information into static KGE methods to accomplish temporal knowledge representations. However, existing static or temporal KGE approaches focus on the single query fact and ignore the query-relevant contextual information in the graph structure. This paper moves beyond the traditional way of scoring facts in distinct vector space and proposes a unified framework with pre-trained language models (PLM) to learn dynamic contextualized static/temporal knowledge graph embeddings, called CoS/TKGE. Given the query-specific subgraph, our model transforms it into an input sequence and uses the PLM to obtain the contextualized knowledge representations, which is flexible adaptive to the input graph contexts. We reformulate the link prediction task as a mask prediction problem to fine-tune the pre-trained language model. And the contrastive learning technique is employed to align dynamic contextual embeddings with static global embeddings. Experimental results on three widely used static and temporal KG datasets show the superiority of our model. © 2014 IEEE.

关键词： Knowledge graph

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Optimizing compiler for shared-memory multiple SIMD architecture 06

Optimizing compiler for shared-memory multiple SIMD architec...

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LCTES 2006 - 2006 ACM SIGPLAN/SIGBED Conference on Languages, Compilers, and Tools for Embedded Systems

作者： Zhang, Weihua Qian, Xinglong Wang, Ye Zang, Binyu Zhu, Chuanqi Parallel Processing Institute Fudan University Shanghai China Architecture Key Lab. Institute of Computing Technology Chinese Academy of Sciences China

ISBN: (纸本)159593362X

With the rapid growth of multimedia and game, these applications put more and more pressure on the processing ability of modern processors. Multiple SIMD architecture is widely used in multimedia processing field as a multimedia accelerator. With the consideration of power consumption and chip size, shared memory multiple SIMD architecture is mainly used in embedded SOCs. In order to further fit mobile environment, there is the constraint of limited register number as well. Although shared memory multiple SIMD architecture simplify the chip design, these constraints are the major obstacles to map the real multimedia applications to these architectures. Until now, to our best knowledge, there is little research on the optimizing techniques for shared memory multiple SIMD architecture. In this paper, we present a compiler framework, which aims at automatically generating high performance codes for shared memory multiple SIMD architecture. In this framework, we reduce the competition of shared data bus through Increasing the register locality, improve the utilization of data bus by read-only data vector replication and solve the problem of limited register number through a resource allocation algorithm. The framework also handlers the issues concerning on data transformation. As the experimental results shown, this framework is successful in mapping real multimedia applications to shared memory multiple SIMD architecture. It leads to an average speedup by a factor of 3.19 and an average utilization of SM-SIMD architecture with 8 SIMD units by a factor of 52.6%. Copyright © 2006 ACM.

关键词： Data storage equipment

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An accelerated block-parallel Newton method via overlapped partitioning

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Lecture Notes in Computational Science and Engineering 2005年 40卷 547-554页

作者： Chen, Yurong Lab. of Parallel Computing Institute of Software CAS China

ISBN: (纸本)3540225234

This paper presents an overlapped block-parallel Newton method for solving large nonlinear systems. The graph partitioning algorithms are first used to partition the Jacobian into weakly coupled overlapping blocks. Then the simplified Newton iteration is directly performed, with the diagonal blocks and the overlapping solutions assembled in a weighted average way at each iteration. In the algorithmic implementation, an accelerated technique has been proposed to reduce the number of iterations. The conditions under which the algorithm is locally and semi-locally convergent are studied. Numerical results from solving power flow equations are presented to support our study.

关键词： Newton-Raphson method

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Strong consistency is not hard to get: Twophase locking and twophase commit on thousands of cores 46th

Strong consistency is not hard to get: Twophase locking and ...

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46th International Conference on Very Large Data Bases, VLDB 2020

作者： Barthels, Claude Müller, Ingo Taranov, Konstantin Alonso, Gustavo Hoefler, Torsten Systems Group Department of Computer Science ETH Zurich Switzerland Scalable Parallel Computing Lab Department of Computer Science ETH Zurich Switzerland

Concurrency control is a cornerstone of distributed database engines and storage systems. In pursuit of scalability, a common assumption is that Two-Phase Locking (2PL) and Two-Phase Commit (2PC) are not viable solutions due to their communication overhead. Recent results, however, have hinted that 2PL and 2PC might not have such a bad performance. Nevertheless, there has been no attempt to actually measure how a state-of-the-art implementation of 2PL and 2PC would perform on modern hardware. The goal of this paper is to establish a baseline for concurrency control mechanisms on thousands of cores connected through a lowlatency network. We develop a distributed lock table supporting all the standard locking modes used in database engines. We focus on strong consistency in the form of strict serializability implemented through strict 2PL, but also explore read-committed and repeatableread, two common isolation levels used in many *** do not leverage any known optimizations in the locking or commit parts of the protocols. The surprising result is that, for TPC-C, 2PL and 2PC can be made to scale to thousands of cores and hundreds of machines, reaching a throughput of over 21 million transactions per second with 9.5 million New Order operations per second. Since most existing relational database engines use some form of locking for implementing concurrency control, our findings provide a path for such systems to scale without having to significantly redesign transaction management. To achieve these results, our implementation relies on Remote Direct Memory Access (RDMA). Today, this technology is commonly available on both Infiniband as well as Ethernet networks, making the results valid across a wide range of systems and platforms, including database appliances, data centers, and cloud environments. © VLDB Endowment.

关键词： Concurrency control

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AUTOSPARSE: TOWARDS AUTOMATED SPARSE TRAINING OF DEEP NEURAL NETWORKS

arXiv

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arXiv 2023年

作者： Kundu, Abhisek Mellempudi, Naveen K. Vooturi, Dharma Teja Kaul, Bharat Dubey, Pradeep Parallel Computing Lab Intel Labs India

Sparse training is emerging as a promising avenue for reducing the computational cost of training neural networks. Several recent studies have proposed pruning methods using learnable thresholds to efficiently explore the non-uniform distribution of sparsity inherent within the models. In this paper, we propose Gradient Annealing (GA), where gradients of masked weights are scaled down in a non-linear manner. GA provides an elegant trade-off between sparsity and accuracy without the need for additional sparsity-inducing regularization. We integrated GA with the latest learnable pruning methods to create an automated sparse training algorithm called AutoSparse, which achieves better accuracy and/or training/inference FLOPS reduction than existing learnable pruning methods for sparse ResNet50 and MobileNetV1 on ImageNet-1K: AutoSparse achieves (2×, 7×) reduction in (training,inference) FLOPS for ResNet50 on ImageNet at 80% sparsity. Finally, AutoSparse outperforms sparse-to-sparse SotA method MEST (uniform sparsity) for 80% sparse ResNet50 with similar accuracy, where MEST uses 12% more training FLOPS and 50% more inference FLOPS. Copyright © 2023, The Authors. All rights reserved.

关键词： Genetic algorithms

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Unravel the rotational and translational behavior of a single squirmer in flexible polymer solutions at different Reynolds numbers

arXiv

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arXiv 2025年

作者： Zhou, Yuan Qi, Kai De Corato, Marco Stratford, Kevin Pagonabarraga, Ignacio 2020 X-Lab Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai200050 China College of Materials Science and Opto-Electronic Technology University of Chinese Academy of Sciences Beijing100049 China Batochime Avenue Forel 2 Lausanne1015 Switzerland University of Zaragoza Zaragoza Spain Edinburgh Parallel Computing Centre The University of Edinburgh The King’s Buildings EdinburghEH9 3JZ United Kingdom Departament de Física de la Matèria Condensada Universitat de Barcelona C. Martí Franquès 1 Barcelona08028 Spain Universitat de Barcelona Barcelona08028 Spain

Microorganisms, such as bacteria and algae, thrive in complex environments and their behavior in fluids holds significant importance for various medical and industrial applications. By conducting Lattice Boltzmann (LB) simulations, the transport and rotational properties of a generic squirmer are investigated in solutions embedded with flexible polymer chains at different Reynolds numbers. The interplay of activity and heterogeneously distributed polymers have profound influences on these properties. Remarkable enhancements of up to three orders of magnitude in the rotational motion, along with apparent decays in self-propelling velocities, are observed for squirmers with nonzero active stresses. These extraordinary phenomena stem from the squirmer-polymer mechanical and hydrodynamic interactions. Specifically, polymer wrapping occurs in front of a pusher, while numerous polymers are absorbed in the rear of a puller. Both mechanisms enhance the rotational motion and simultaneously impede translations through forces and torques arising from direct contacts or asymmetric local flows induced by polymers. The source dipole flow fields generated by a neutral swimmer rapidly advect polymers to the rear, leaving no apparent impacts on its rotational and transport properties. The influences of Reynolds number Re (Re=0.8 and 0.04) and squirmer-polymer boundary conditions (no-slip and repulsive) on the dynamics are addressed. In short, the no-slip boundary condition results in more profound effects on both rotational and translational properties at Re = 0.8. However, at Re = 0.04, the disparity between the two boundary conditions diminishes due to the heightened fluid viscous drag, which impedes direct contacts between squirmers and polymers. Our results reveal the relevance of system heterogeneity and highlight the essential role of squirmer-polymer mechanical and hydrodynamic interactions in shaping the behavior of swimmers in viscoelastic fluids. These findings offer valua

关键词： Reynolds number

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PRACTICAL MASSIVELY parallel MONTE-CARLO TREE SEARCH APPLIED TO MOLECULAR DESIGN 9

PRACTICAL MASSIVELY PARALLEL MONTE-CARLO TREE SEARCH APPLIED...

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9th International Conference on Learning Representations, ICLR 2021

作者： Yang, Xiufeng Aasawat, Tanuj Kr Yoshizoe, Kazuki Chugai Pharmaceutical Co. Ltd Japan Parallel Computing Lab - India Intel Labs India RIKEN Center for Advanced Intelligence Project Japan

It is common practice to use large computational resources to train neural networks, known from many examples, such as reinforcement learning applications. However, while massively parallel computing is often used for training models, it is rarely used to search solutions for combinatorial optimization problems. This paper proposes a novel massively parallel Monte-Carlo Tree Search (MP-MCTS) algorithm that works efficiently for a 1,000 worker scale on a distributed memory environment using multiple compute nodes and applies it to molecular design. This paper is the first work that applies distributed MCTS to a real-world and non-game problem. Existing works on large-scale parallel MCTS show efficient scalability in terms of the number of rollouts up to 100 workers. Still, they suffer from the degradation in the quality of the solutions. MP-MCTS maintains the search quality at a larger scale. By running MP-MCTS on 256 CPU cores for only 10 minutes, we obtained candidate molecules with similar scores to non-parallel MCTS running for 42 hours. Moreover, our results based on parallel MCTS (combined with a simple RNN model) significantly outperform existing state-of-the-art work. Our method is generic and is expected to speed up other applications of MCTS. © 2021 ICLR 2021 - 9th International Conference on Learning Representations. All rights reserved.

关键词： Reinforcement learning

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EvAnT: Analysis and checking of event traces for wireless sensor networks

EvAnT: Analysis and checking of event traces for wireless se...

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2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy computing, SUTC 2008

作者： Woehrle, Matthias Plessl, Christian Lim, Roman Beutel, Jan Thiele, Lothar ETH Zurich Computer Engineering and Networks Lab. 8092 Zurich Switzerland University of Paderborn Paderborn Center for Parallel Computing 33102 Paderborn Germany

ISBN: (纸本)9780769531588

Testing and verification methodologies for Wireless Sensor Networks (WSN) systems in pre-deployment are vital for a successful deployment. Increased visibility of the internal state of a WSN application is established by instrumenting the application for logging execution traces at runtime. While the interpretation of the event traces is application-specific, a common method for analysis can be devised. This method should allow for a concise formulation of explorative queries to determine the occurrence and the cause of functional or performance problems. The contribution of this paper is an event analysis methodology that is implemented in the EvAnT framework. EvAnT allows for specifying queries that are executed on the collected traces. EvAnT is specifically tailored to WSN testing and debugging. We demonstrate the applicability of EvAnT by a case study in a building monitoring project. © 2008 IEEE.

关键词： Wireless sensor networks

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