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A modern GPU aims to simultaneously execute more warps for higher Thread-Level Parallelism (TLP) and performance. When generating many memory requests, however, warps contend for limited cache space and thrash cache, which in turn severely…

Hardware Architecture · Computer Science 2018-05-22 Jie Zhang , Shuwen Gao , Nam Sung Kim , Myoungsoo Jung

Scheduling real-time tasks that utilize GPUs with analyzable guarantees poses a significant challenge due to the intricate interaction between CPU and GPU resources, as well as the complex GPU hardware and software stack. While much…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-06-11 Yidi Wang , Cong Liu , Daniel Wong , Hyoseung Kim

Large language models (LLMs) demand significant memory and computation resources. Wafer-scale chips (WSCs) provide high computation power and die-to-die (D2D) bandwidth but face a unique trade-off between on-chip memory and compute…

Hardware Architecture · Computer Science 2025-12-17 Huizheng Wang , Taiquan Wei , Zichuan Wang , Dingcheng Jiang , Qize Yang , Jiaxin Liu , Jingxiang Hou , Chao Li , Jinyi Deng , Yang Hu , Shouyi Yin

Stochastic simulations need multiple replications in order to build confidence intervals for their results. Even if we do not need a large amount of replications, it is a good practice to speed-up the whole simulation time using the…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-01-08 Jonathan Passerat-Palmbach , Jonathan Caux , Pridi Siregar , Claude Mazel , David Hill

In a modern GPU architecture, all threads within a warp execute the same instruction in lockstep. For a memory instruction, this can lead to memory divergence: the memory requests for some threads are serviced early, while the remaining…

Hardware Architecture · Computer Science 2018-05-01 Rachata Ausavarungnirun , Saugata Ghose , Onur Kayıran , Gabriel H. Loh , Chita R. Das , Mahmut T. Kandemir , Onur Mutlu

GPU hash tables are increasingly used to accelerate data processing, but their limited functionality restricts adoption in large-scale data processing applications. Current limitations include incomplete concurrency support and missing…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-24 Hunter McCoy , Prashant Pandey

As Large Language Models (LLMs) become increasingly accessible to end users, an ever-growing number of inference requests are initiated from edge devices and computed on centralized GPU clusters. However, the resulting exponential growth in…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-04-08 Xiangchen Li , Jiakun Fan , Qingyuan Wang , Dimitrios Spatharakis , Saeid Ghafouri , Hans Vandierendonck , Deepu John , Bo Ji , Ali R. Butt , Dimitrios S. Nikolopoulos

The push-relabel algorithm is an efficient algorithm that solves the maximum flow/ minimum cut problems of its affinity to parallelization. As the size of graphs grows exponentially, researchers have used Graphics Processing Units (GPUs) to…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-04-02 Chou-Ying Hsieh , Po-Chieh Lin , Sy-Yen Kuo

The Streaming Multiprocessors (SMs) of a Graphics Processing Unit (GPU) execute instructions from a group of consecutive threads, called warps. At each cycle, an SM schedules a warp from a group of active warps and can context switch among…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-12-13 Jayvant Anantpur , Nagendra Gulur Dwarakanath , Shivaram Kalyanakrishnan , Shalabh Bhatnagar , R. Govindarajan

Domain-specific languages that execute image processing pipelineson GPUs, such as Halide and Forma, operate by 1) dividing the image into overlapped tiles, and 2) fusing loops to improve memory locality. However, current approaches have…

Programming Languages · Computer Science 2020-09-09 Abhinav Jangda , Arjun Guha

The single-source shortest path (SSSP) problem is a well-studied problem that is used in many applications. In the parallel setting, a work-efficient algorithm that additionally attains $o(n)$ parallel depth has been elusive. Alternatively,…

Data Structures and Algorithms · Computer Science 2023-05-15 Kyle Berney , John Iacono , Ben Karsin , Nodari Sitchinava

Parallel programming models can encourage performance portability by moving the responsibility for work assignment and data distribution from the programmer to a runtime system. However, analyzing the resulting implicit memory allocations,…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-03-14 Fabian Knorr , Philip Salzmann , Peter Thoman , Thomas Fahringer

The continued growth of the computational capability of throughput processors has made throughput processors the platform of choice for a wide variety of high performance computing applications. Graphics Processing Units (GPUs) are a prime…

Hardware Architecture · Computer Science 2018-05-01 Rachata Ausavarungnirun

GPGPU applications exploit on-chip scratchpad memory available in the Graphics Processing Units (GPUs) to improve performance. The amount of thread level parallelism present in the GPU is limited by the number of resident threads, which in…

Hardware Architecture · Computer Science 2017-02-14 Vishwesh Jatala , Jayvant Anantpur , Amey Karkare

GPU architectures have continued to grow in complexity, with recent incarnations introducing increasingly powerful fixed-function units for matrix multiplication and data movement to accompany highly parallel general-purpose cores. To fully…

Programming Languages · Computer Science 2025-12-23 Rupanshu Soi , Rohan Yadav , Fredrik Kjolstad , Alex Aiken , Maryam Mehri Dehnavi , Michael Garland , Michael Bauer

GPUs are vastly underutilized, even when running resource-intensive AI applications, as GPU kernels within each job have diverse resource profiles that may saturate some parts of a device while often leaving other parts idle. Colocating…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-02-17 Paul Elvinger , Foteini Strati , Natalie Enright Jerger , Ana Klimovic

GPUs exploit a high degree of thread-level parallelism to hide long-latency stalls. Due to the heterogeneous compute requirements of different applications, there is a growing need to share the GPU across multiple applications in…

In real-time Visual SLAM systems, local mapping must operate under strict latency constraints, as delays degrade map quality and increase the risk of tracking failure. GPU parallelization offers a promising way to reduce latency. However,…

In this paper we describe HeSP, a complete simulation framework to study a general task scheduling-partitioning problem on heterogeneous architectures, which treats recursive task partitioning and scheduling decisions on equal footing.…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-02-18 Anton Rey , Francisco D. Igual , Manuel Prieto-Matías

The increasing number of rectilinear floorplans in modern chip designs presents significant challenges for traditional macro placers due to the additional complexity introduced by blocked corners. Particularly, the widely adopted wirelength…

Hardware Architecture · Computer Science 2025-05-22 Xiaotian Zhao , Zixuan Li , Yichen Cai , Xinfei Guo
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