Suchergebnisse - parallel computing algorithm

Skywalker: Efficient Alias-Method-Based Graph Sampling and Random Walk on GPUs von 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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SFLU: Synchronization-Free Sparse LU Factorization for Fast Circuit Simulation on GPUs von Zhao, Jianqi, Wen, Yao, Luo, Yuchen, Jin, Zhou, Liu, Weifeng, Zhou, Zhenya

“… Sparse LU factorization is one of the key building blocks of sparse direct solvers and often dominates the computing time of circuit simulation programs …”
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Parallelizing Maximal Clique Enumeration on GPUs von 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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MAD-Max Beyond Single-Node: Enabling Large Machine Learning Model Acceleration on Distributed Systems von Hsia, Samuel, Golden, Alicia, Acun, Bilge, Ardalani, Newsha, DeVito, Zachary, Wei, Gu-Yeon, Brooks, David, Wu, Carole-Jean

“… Training and deploying large-scale machine learning models is time-consuming, requires significant distributed computing infrastructures, and incurs high operational costs …”
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pSyncPIM: Partially Synchronous Execution of Sparse Matrix Operations for All-Bank PIM Architectures von Baek, Daehyeon, Hwang, Soojin, Huh, Jaehyuk

“… Recent commercial incarnations of processing-in-memory (PIM) maintain the standard DRAM interface and employ the all-bank mode execution to maximize bank-level …”
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Leveraging Difference Recurrence Relations for High-Performance GPU Genome Alignment von Zeni, Alberto, Onken, Seth, Santambrogio, Marco Domenico, Samadi, Mehrzad

“… while decreasing the associated cost, emphasizing the need for fast and accurate software to perform sequence analysis, given the quadratic complexity of exact pairwise algorithms …”
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HybriMoE: Hybrid CPU-GPU Scheduling and Cache Management for Efficient MoE Inference von Zhong, Shuzhang, Sun, Yanfan, Liang, Ling, Wang, Runsheng, Huang, Ru, Li, Meng

“… The Mixture of Experts (MoE) architecture has demonstrated significant advantages as it enables to increase the model capacity without a proportional increase …”
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Seer: Predictive Runtime Kernel Selection for Irregular Problems von Swann, Ryan, Osama, Muhammad, Sangaiah, Karthik, Mahmud, Jalal

“… Modern GPUs are designed for regular problems and suffer from load imbalance when processing irregular data. Prior to our work, a domain expert selects the …”
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NDFT: Accelerating Density Functional Theory Calculations via Hardware/Software Co-Design on Near-Data Computing System von Jiang, Qingcai, Tu, Buxin, Hao, Xiaoyu, Chen, Junshi, An, Hong

“… Linear-response time-dependent Density Functional Theory (LR-TDDFT) is a widely used method for accurately predicting the excited-state properties of physical …”
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TSUNAMI: A GPU Implementation of the WFA Algorithm von Gerometta, Giulia, Zeni, Alberto, Santambrogio, Marco D.

“… TSUNAMI exploits GPU high-parallel computing to accelerate …”
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Accelerating Fourier and Number Theoretic Transforms using Tensor Cores and Warp Shuffles von Durrani, Sultan, Chughtai, Muhammad Saad, Hidayetoglu, Mert, Tahir, Rashid, Dakkak, Abdul, Rauchwerger, Lawrence, Zaffar, Fareed, Hwu, Wen-mei

“… To speed things up, fast Fourier transform (FFT) algorithms, which are reduced-complexity formulations for computing the DFT of a sequence, have been proposed and implemented for traditional processors and their corresponding instruction sets …”
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DenSparSA: A Balanced Systolic Array Approach for Dense and Sparse Matrix Multiplication von Wang, Ziheng, Sun, Ruiqi, He, Xin, Ma, Tianrui, Zou, An

“… Numerous studies have proposed hardware architectures to accelerate sparse matrix multiplication, but these approaches often incur substantial area and power …”
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OpenDRC: An Efficient Open-Source Design Rule Checking Engine with Hierarchical GPU Acceleration von He, Zhuolun, Zuo, Yihang, Jiang, Jiaxi, Zheng, Haisheng, Ma, Yuzhe, Yu, Bei

“… OpenDRC maintains hierarchical layouts with layer-wise bounding volume hierarchies and performs adaptive row-based partition to identify independent regions for check pruning and/or parallel processing …”
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Gluon-Async: A Bulk-Asynchronous System for Distributed and Heterogeneous Graph Analytics von Dathathri, Roshan, Gill, Gurbinder, Hoang, Loc, Jatala, Vishwesh, Pingali, Keshav, Nandivada, V. Krishna, Dang, Hoang-Vu, Snir, Marc

“… Distributed graph analytics systems for CPUs, like D-Galois and Gemini, and for GPUs, like D-IrGL and Lux, use a bulk-synchronous parallel (BSP …”
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New sequential and parallel algorithms for computing the β-spectrum von Kowaluk, Mirosław, Majewska, Gabriela

“… <p<∞. We present an O(nlog2⁡n) time sequential, and an O(log4⁡n) time parallel, β-spectrum labeling. We also show a parallel algorithm, which for a …”
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DARIS: An Oversubscribed Spatio-Temporal Scheduler for Real-Time DNN Inference on GPUs von Babaei, Amir Fakhim, Chantem, Thidapat

“… In particular, DARIS improves GPU utilization and uniquely analyzes GPU concurrency by oversubscribing computing resources …”
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Ultra Efficient Acceleration for De Novo Genome Assembly via Near-Memory Computing von Zhou, Minxuan, Wu, Lingxi, Li, Muzhou, Moshiri, Niema, Skadron, Kevin, Rosing, Tajana

“… De novo assembly of genomes for which there is no reference, is essential for novel species discovery and metagenomics. In this work, we accelerate two key …”
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SpV8: Pursuing Optimal Vectorization and Regular Computation Pattern in SpMV von Li, Chenyang, Xia, Tian, Zhao, Wenzhe, Zheng, Nanning, Ren, Pengju

“… We evaluate SpV8 on Intel Xeon CPU and compare with multiple state-of-art SpMV algorithms using 71 sparse matrices …”
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Versatile Cross-platform Compilation Toolchain for Schrödinger-style Quantum Circuit Simulation von Lu, Yuncheng, Liang, Shuang, Fan, Hongxiang, Guo, Ce, Luk, Wayne, Kelly, Paul H. J.

“… While existing quantum hardware resources have limited availability and reliability, there is a growing demand for exploring and verifying quantum algorithms …”
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Max-PIM: Fast and Efficient Max/Min Searching in DRAM von Zhang, Fan, Angizi, Shaahin, Fan, Deliang

“… In this work, for the first time, we propose a novel 'Min/Max-in-memory' algorithm based on iterative XNOR bit-wise comparison, which supports parallel inmemory searching for minimum and maximum …”
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