Výsledky vyhľadávania - "Computing methodologies → Parallel computing methodologies"

SFLU: Synchronization-Free Sparse LU Factorization for Fast Circuit Simulation on GPUs Autor 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 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. Prior works…”
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TSUNAMI: A GPU Implementation of the WFA Algorithm Autor Gerometta, Giulia, Zeni, Alberto, Santambrogio, Marco D.

“…Pairwise sequence alignment represents a fundamental step in the genome assembly pipeline, being the most time-consuming step and the bottleneck factor in…”
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PID-Comm: A Fast and Flexible Collective Communication Framework for Commodity Processing-in-DIMM Devices Autor Noh, Si Ung, Hong, Junguk, Lim, Chaemin, Park, Seongyeon, Kim, Jeehyun, Kim, Hanjun, Kim, Youngsok, Lee, Jinho

“…Recent dual in-line memory modules (DIMMs) are starting to support processing-in-memory (PIM) by associating their memory banks with processing elements (PEs),…”
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Versatile Cross-platform Compilation Toolchain for Schrödinger-style Quantum Circuit Simulation Autor 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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DARIS: An Oversubscribed Spatio-Temporal Scheduler for Real-Time DNN Inference on GPUs Autor Babaei, Amir Fakhim, Chantem, Thidapat

“…The widespread use of Deep Neural Networks (DNNs) is limited by high computational demands, especially in constrained environments. GPUs, though effective…”
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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…”
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MAD-Max Beyond Single-Node: Enabling Large Machine Learning Model Acceleration on Distributed Systems Autor 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…”
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Splitwise: Efficient Generative LLM Inference Using Phase Splitting Autor Patel, Pratyush, Choukse, Esha, Zhang, Chaojie, Shah, Aashaka, Goiri, Inigo, Maleki, Saeed, Bianchini, Ricardo

“…Generative large language model (LLM) applications are growing rapidly, leading to large-scale deployments of expensive and power-hungry GPUs. Our…”
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HybriMoE: Hybrid CPU-GPU Scheduling and Cache Management for Efficient MoE Inference Autor 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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DenSparSA: A Balanced Systolic Array Approach for Dense and Sparse Matrix Multiplication Autor 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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NDFT: Accelerating Density Functional Theory Calculations via Hardware/Software Co-Design on Near-Data Computing System Autor 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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OpenDRC: An Efficient Open-Source Design Rule Checking Engine with Hierarchical GPU Acceleration Autor He, Zhuolun, Zuo, Yihang, Jiang, Jiaxi, Zheng, Haisheng, Ma, Yuzhe, Yu, Bei

“…Design rule checking (DRC) is an essential procedure in physical verification, yet few open-source DRC tools are accessible in academia. To fill in the gap, we…”
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Polygeist: Raising C to Polyhedral MLIR Autor Moses, William S., Chelini, Lorenzo, Zhao, Ruizhe, Zinenko, Oleksandr

“…We present Polygeist, a new compilation flow that connects the MLIR compiler infrastructure to cutting edge polyhedral optimization tools. It consists of a C…”
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pSyncPIM: Partially Synchronous Execution of Sparse Matrix Operations for All-Bank PIM Architectures Autor 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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Scalpel: Customizing DNN pruning to the underlying hardware parallelism Autor Jiecao Yu, Lukefahr, Andrew, Palframan, David, Dasika, Ganesh, Das, Reetuparna, Mahlke, Scott

“…As the size of Deep Neural Networks (DNNs) continues to grow to increase accuracy and solve more complex problems, their energy footprint also scales. Weight…”
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Leveraging Difference Recurrence Relations for High-Performance GPU Genome Alignment Autor Zeni, Alberto, Onken, Seth, Santambrogio, Marco Domenico, Samadi, Mehrzad

“…Genome pairwise sequence alignment is one of the most computationally intensive workloads in many genomic pipelines, often accounting for over 90% of the…”
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Accelerating Fourier and Number Theoretic Transforms using Tensor Cores and Warp Shuffles Autor Durrani, Sultan, Chughtai, Muhammad Saad, Hidayetoglu, Mert, Tahir, Rashid, Dakkak, Abdul, Rauchwerger, Lawrence, Zaffar, Fareed, Hwu, Wen-mei

“…The discrete Fourier transform (DFT) and its specialized case, the number theoretic transform (NTT), are two important mathematical tools having applications…”
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SimplePIM: A Software Framework for Productive and Efficient Processing-in-Memory Autor Chen, Jinfan, Gomez-Luna, Juan, El Hajj, Izzat, Guo, Yuxin, Mutlu, Onur

“…Data movement between memory and processors is a major bottleneck in modern computing systems. The processing-in-memory (PIM) paradigm aims to alleviate this…”
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Seer: Predictive Runtime Kernel Selection for Irregular Problems Autor 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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