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相关论文: SKaMPI-OpenSHMEM: Measuring OpenSHMEM Communicatio…

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This document presents the OpenSHMEM extension for the Special Karlsruhe MPI benchmark and the measurement algorithms used to measure the routines.

分布式、并行与集群计算 · 计算机科学 2021-05-31 Camille Coti , Allen D Malony

The Message Passing Interface (MPI) is the prevalent programming model used on today's supercomputers. Therefore, MPI library developers are looking for the best possible performance (shortest run-time) of individual MPI functions across…

分布式、并行与集群计算 · 计算机科学 2016-05-30 Sascha Hunold , Alexandra Carpen-Amarie

The Message Passing Interface (MPI) is the most commonly used application programming interface for process communication on current large-scale parallel systems. Due to the scale and complexity of modern parallel architectures, it is…

分布式、并行与集群计算 · 计算机科学 2016-09-05 Sascha Hunold , Alexandra Carpen-Amarie , Felix Donatus Lübbe , Jesper Larsson Träff

Temporal reasoning and planning are essential capabilities for large language models (LLMs), yet most existing benchmarks evaluate them in isolation and under limited forms of complexity. To address this gap, we introduce the Temporal…

人工智能 · 计算机科学 2025-10-14 Zifeng Ding , Sikuan Yan , Zhangdie Yuan , Xianglong Hu , Fangru Lin , Andreas Vlachos

The current trend of multicore architectures on shared memory systems underscores the need of parallelism. While there are some programming model to express parallelism, thread programming model has become a standard to support these system…

分布式、并行与集群计算 · 计算机科学 2010-12-13 D. T. Hasta , A. B. Mutiara

Python has become a dominant programming language for emerging areas like Machine Learning (ML), Deep Learning (DL), and Data Science (DS). An attractive feature of Python is that it provides easy-to-use programming interface while allowing…

分布式、并行与集群计算 · 计算机科学 2022-08-26 Nawras Alnaasan , Arpan Jain , Aamir Shafi , Hari Subramoni , Dhabaleswar K Panda

Benchmarking involves designing, running and disseminating rigorous performance assessments of methods, most often for data analysis and software tools, but the process can also be applied to experimental systems. Ideally, a benchmarking…

The paper introduces PDSP-Bench, a novel benchmarking system designed for a systematic understanding of performance of parallel stream processing in a distributed environment. Such an understanding is essential for determining how Stream…

分布式、并行与集群计算 · 计算机科学 2025-04-16 Pratyush Agnihotri , Boris Koldehofe , Roman Heinrich , Carsten Binnig , Manisha Luthra

Comprehending the performance bottlenecks at the core of the intricate hardware-software interactions exhibited by highly parallel programs on HPC clusters is crucial. This paper sheds light on the issue of automatically asynchronous MPI…

分布式、并行与集群计算 · 计算机科学 2023-09-06 Ayesha Afzal , Georg Hager , Stefano Markidis , Gerhard Wellein

Benchmarking is an important measure for companies to investigate their performance and to increase efficiency. As companies usually are reluctant to provide their key performance indicators (KPIs) for public benchmarks, privacy-preserving…

密码学与安全 · 计算机科学 2019-03-28 Kilian Becher , Martin Beck , Thorsten Strufe

While application profiling has been a mainstay in the HPC community for years, profiling of MPI and other communication middleware has not received the same degree of exploration. This paper adds to the discussion of MPI profiling,…

分布式、并行与集群计算 · 计算机科学 2024-02-20 Riley Shipley , Garrett Hooten , David Boehme , Derek Schafer , Anthony Skjellum , Olga Pearce

The cloud infrastructure must provide security for High-Performance Computing (HPC) applications of sensitive data to execute in such an environment. However, supporting security in the communication infrastructure of today's public cloud…

分布式、并行与集群计算 · 计算机科学 2020-11-04 Abu Naser , Cong Wu , Mehran Sadeghi Lahijani , Mohsen Gavahi , Viet Tung Hoang , Zhi Wang , Xin Yuan

The trend towards highly parallel multi-processing is ubiquitous in all modern computer architectures, ranging from handheld devices to large-scale HPC systems; yet many applications are struggling to fully utilise the multiple levels of…

分布式、并行与集群计算 · 计算机科学 2013-07-19 Michael Lange , Gerard Gorman , Michele Weiland , Lawrence Mitchell , Xiaohu Guo , James Southern

Optimizing scientific applications to take full advan-tage of modern memory subsystems is a continual challenge forapplication and compiler developers. Factors beyond working setsize affect performance. A benchmark framework that…

性能 · 计算机科学 2018-12-20 Mahesh Lakshminarasimhan , Catherine Olschanowsky

An increasing number of organizations are deploying Large Language Models (LLMs) for a wide range of tasks. Despite their general utility, LLMs are prone to errors, ranging from inaccuracies to hallucinations. To objectively assess the…

人工智能 · 计算机科学 2024-10-15 Kiran Busch , Henrik Leopold

Recent advancements in data stream processing frameworks have improved real-time data handling, however, scalability remains a significant challenge affecting throughput and latency. While studies have explored this issue on local machines…

分布式、并行与集群计算 · 计算机科学 2025-04-04 Apurv Deepak Kulkarni , Siavash Ghiasvand

The progression of communication in the Message Passing Interface (MPI) is not well defined, yet it is critical for application performance, particularly in achieving effective computation and communication overlap. The opaque nature of MPI…

分布式、并行与集群计算 · 计算机科学 2024-07-16 Hui Zhou , Robert Latham , Ken Raffenetti , Yanfei Guo , Rajeev Thakur

Despite the various research initiatives and proposed programming models, efficient solutions for parallel programming in HPC clusters still rely on a complex combination of different programming models (e.g., OpenMP and MPI), languages…

The increasing complexity of HPC architectures and the growing adoption of irregular scientific algorithms demand efficient support for asynchronous, multithreaded communication. This need is especially pronounced with Asynchronous…

分布式、并行与集群计算 · 计算机科学 2025-08-27 Jiakun Yan , Marc Snir , Yanfei Guo
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