Výsledky vyhledávání - Theory of computation - Design and analysis of algorithms

Late Breaking Results: An Efficient and Scalable Track Assignment with GPU Parallelism Autor Liu, Genggeng, Huang, Pengcheng, Li, Zepeng, Liu, Wen-Hao, Huang, Xing, Guo, Wenzhong

“… Based on the independence and divisibility of track assignment, we propose a GPU-accelerated parallel track assignment algorithm…”
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DS-GL: Advancing Graph Learning via Harnessing Nature's Power within Scalable Dynamical Systems Autor Song, Ruibing, Wu, Chunshu, Liu, Chuan, Li, Ang, Huang, Michael, Geng, Tony Tong

“… problems and have been adopted for traditional graph computation, such as max-cut. However, when performing complex Graph Learning (GL…”
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Invited: Algorithms and Architectures for Accelerating Long Read Sequence Analysis Autor Gamaarachchi, Hasindu, Liyanage, Kisaru, Parameswaran, Sri

“…; and three, novel algorithms and domain-specific architectures for rapid in situ analysis of third-generation sequencing data…”
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Optimal Memory Allocation and Scheduling for DMA Data Transfers under the LET Paradigm Autor Pazzaglia, Paolo, Casini, Daniel, Biondi, Alessandro, Natale, Marco Di

“…The Logical Execution Time (LET) paradigm is increasingly used to achieve predictable communications in modern multicore automotive applications. Direct Memory…”
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Skywalker: Efficient Alias-Method-Based Graph Sampling and Random Walk on GPUs Autor Wang, Pengyu, Li, Chao, Wang, Jing, Wang, Taolei, Zhang, Lu, Leng, Jingwen, Chen, Quan, Guo, Minyi

“…Graph sampling and random walk operations, capturing the structural properties of graphs, are playing an important role today as we cannot directly adopt computing-intensive algorithms on large-scale graphs…”
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BlasPart: A Deterministic Parallel Partitioner for Balanced Large-Scale Hypergraph Partitioning Autor Tong, Shengbo, Pei, Chunyan, Yu, Wenjian

“…Balanced hypergraph partitioning is a fundamental problem in applications like VLSI design, high-performance computing, etc…”
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ParGNN: A Scalable Graph Neural Network Training Framework on multi-GPUs Autor Gu, Junyu, Li, Shunde, Cao, Rongqiang, Wang, Jue, Wang, Zijian, Liang, Zhiqiang, Liu, Fang, Li, Shigang, Zhou, Chunbao, Wang, Yangang, Chi, Xuebin

“… over-partition to alleviate load imbalance. Based on the over-partition results, we present a subgraph pipeline algorithm to overlap communication and computation while maintaining the accuracy of GNN training…”
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PertNAS: Architectural Perturbations for Memory-Efficient Neural Architecture Search Autor Ahmad, Afzal, Xie, Zhiyao, Zhang, Wei

“… This leads to GPU-memory bottlenecks that hamper the algorithm's scalability. To resolve these bottlenecks, we propose a perturbations-based evolutionary approach…”
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BLESS: Bandwidth and Locality Enhanced SMEM Seeding Acceleration for DNA Sequencing Autor Han, Seunghee, Moon, Seungjae, Suh, Teokkyu, Heo, JaeHoon, Kim, Joo-Young

“… The seeding process, which aims to find locations of super-maximal exact matches (SMEM) between the DNA samples and reference genome for comparative analysis, has emerged as a major bottleneck due to its memory-intensive characteristics…”
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A Universal Method for Task Allocation on FP-FPS Multiprocessor Systems with Spin Locks Autor Zhao, Shuai, Chen, Nan, Fang, Yinjie, Li, Zhao, Chang, Wanli

“… Unfortunately, these existing methods either are tailored for specific scheduling and analysis approaches, or introduce runtime overhead that undermines their applicability…”
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ACGraph: Accelerating Streaming Graph Processing via Dependence Hierarchy Autor Jiang, Zihan, Mao, Fubing, Guo, Yapu, Liu, Xu, Liu, Haikun, Liao, Xiaofei, Jin, Hai, Zhang, Wei

“…Streaming graph processing needs to timely evaluate continuous queries. Prior systems suffer from massive redundant computations due to the irregular order of processing vertices influenced by updates…”
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GARL: Genetic Algorithm-Augmented Reinforcement Learning to Detect Violations in Marker-Based Autonomous Landing Systems Autor Liang, Linfeng, Deng, Yao, Morton, Kye, Kallinen, Valtteri, James, Alice, Seth, Avishkar, Kuantama, Endrowednes, Mukhopadhyay, Subhas, Han, Richard, Zheng, Xi

“… To address these issues, we introduce GARL, a framework combining a genetic algorithm (GA) and reinforcement learning (RL…”
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Parallelizing Maximal Clique Enumeration on GPUs Autor Almasri, Mohammad, Chang, Yen-Hsiang, Hajj, Izzat El, Nagi, Rakesh, Xiong, Jinjun, Hwu, Wen-mei

“…We present a GPU solution for exact maximal clique enumeration (MCE) that performs a search tree traversal following the Bron-Kerbosch algorithm…”
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SumPA: Efficient Pattern-Centric Graph Mining with Pattern Abstraction Autor Gui, Chuangyi, Liao, Xiaofei, Zheng, Long, Yao, Pengcheng, Wang, Qinggang, Jin, Hai

“…Graph mining aims to explore interesting structural information of a graph. Pattern-centric systems typically transform a generic-purpose graph mining problem…”
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Placement Tomography-Based Routing Blockage Generation for DRV Hotspot Mitigation Autor Kahng, Andrew B., Kundu, Sayak, Yoon, Dooseok

“…A fundamental goal in modern physical design is for the post-route layout to have a fixable number of remaining design rule violations (DRVs…”
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Asynchronous Distributed-Memory Parallel Algorithms for Influence Maximization Autor Singhal, Shubhendra Pal, Hati, Souvadra, Young, Jeffrey, Sarkar, Vivek, Hayashi, Akihiro, Vuduc, Richard

“… We propose distributed-memory parallel algorithms for the two main kernels of a state-of-the-art implementation of one IM algorithm, influence maximization via martingales (IMM…”
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InnerSP: A Memory Efficient Sparse Matrix Multiplication Accelerator with Locality-Aware Inner Product Processing Autor Baek, Daehyeon, Hwang, Soojin, Heo, Taekyung, Kim, Daehoon, Huh, Jaehyuk

“… To mitigate the memory access overheads, recent accelerator designs advocated the outer product processing which minimizes input accesses but generates intermediate products to be merged to the final output matrix…”
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NEO-DNND: Communication-Optimized Distributed Nearest Neighbor Graph Construction Autor Iwabuchi, Keita, Steil, Trevor, Priest, Benjamin W., Pearce, Roger, Sanders, Geoffrey

“…Graph-based approximate nearest neighbor algorithms have shown high neighbor structure representation quality…”
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BLOwing Trees to the Ground: Layout Optimization of Decision Trees on Racetrack Memory Autor Hakert, Christian, Khan, Asif Ali, Chen, Kuan-Hsun, Hameed, Fazal, Castrillon, Jeronimo, Chen, Jian-Jia

“…Modern distributed low power systems tend to integrate machine learning algorithms, which are directly executed on the distributed devices (on the edge…”
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Network-Offloaded Bandwidth-Optimal Broadcast and Allgather for Distributed AI Autor Khalilov, Mikhail, Girolamo, Salvatore Di, Chrapek, Marcin, Nudelman, Rami, Bloch, Gil, Hoefler, Torsten

“…In the Fully Sharded Data Parallel (FSDP) training pipeline, collective operations can be interleaved to maximize the communication/computation overlap…”
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