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Large Language Models (LLMs) are consistently improving at increasingly realistic software engineering (SE) tasks. In real-world software stacks, significant SE effort is spent developing foundational system software like the Linux kernel.…

Software Engineering · Computer Science 2024-11-13 Alex Mathai , Chenxi Huang , Petros Maniatis , Aleksandr Nogikh , Franjo Ivancic , Junfeng Yang , Baishakhi Ray

We introduce a user mode file system, CannyFS, that hides latency by assuming all I/O operations will succeed. The user mode process will in turn report errors, allowing proper cleanup and a repeated attempt to take place. We demonstrate…

Operating Systems · Computer Science 2016-12-21 Jessica Nettelblad , Carl Nettelblad

In this report we present a network-level multi-core energy model and a software development process workflow that allows software developers to estimate the energy consumption of multi-core embedded programs. This work focuses on a high…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-09-10 Steve Kerrison , Kerstin Eder

Most commercial embedded devices have been deployed with a single processor architecture. The code size and complexity of applications running on embedded devices are rapidly increasing due to the emergence of application business models…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-01-26 Geunsik Lim , Changwoo Min , YoungIk Eom

As memory capacity has outstripped TLB coverage, large data applications suffer from frequent page table walks. We investigate two complementary techniques for addressing this cost: reducing the number of accesses required and reducing the…

Hardware Architecture · Computer Science 2021-09-03 Chang Hyun Park , Ilias Vougioukas , Andreas Sandberg , David Black-Schaffer

High-performance scientific applications require more and more compute power. The concurrent use of multiple distributed compute resources is vital for making scientific progress. The resulting distributed system, a so-called Jungle…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-03-05 Niels Drost , Jason Maassen , Maarten A. J. van Meersbergen , Henri E. Bal , F. Inti Pelupessy , Simon Portegies Zwart , Michael Kliphuis , Henk A. Dijkstra , Frank J. Seinstra

I/O efficiency is crucial to productivity in scientific computing, but the increasing complexity of the system and the applications makes it difficult for practitioners to understand and optimize I/O behavior at scale. Data-driven machine…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-04-19 Mihailo Isakov , Mikaela Currier , Eliakin del Rosario , Sandeep Madireddy , Prasanna Balaprakash , Philip Carns , Robert B. Ross , Glenn K. Lockwood , Michel A. Kinsy

In the past couple of decades, the computational abilities of supercomput- ers have increased tremendously. Leadership scale supercomputers now are capable of petaflops. Likewise, the problem size targeted by applications running on such…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-09-06 Robert Louis Cloud

Optimal use of computing resources requires extensive coding, tuning and benchmarking. To boost developer productivity in these time consuming tasks, we introduce the Experimental Linear Algebra Performance Studies framework (ELAPS), a…

Performance · Computer Science 2015-05-01 Elmar Peise , Paolo Bientinesi

Meeting performance and scalability requirements while delivering services is a critical issue in web applications. Recently, latency and cost of Internet-based services are encouraging the use of application-level caching to continue…

Software Engineering · Computer Science 2020-11-03 Jhonny Mertz , Ingrid Nunes

Large-scale HPC simulations of plasma dynamics in fusion devices require efficient parallel I/O to avoid slowing down the simulation and to enable the post-processing of critical information. Such complex simulations lacking parallel I/O…

As large language models (LLMs) have shown great success in many tasks, they are used in various applications. While a lot of works have focused on the efficiency of single-LLM application (e.g., offloading, request scheduling, parallelism…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-03-24 Jingzhi Fang , Yanyan Shen , Yue Wang , Lei Chen

Large Language Models (LLMs) are increasingly deployed in large-scale online services, enabling sophisticated applications. However, the computational overhead of generating key-value (KV) caches in the prefill stage presents a major…

Machine Learning · Computer Science 2025-02-24 Shuowei Jin , Xueshen Liu , Qingzhao Zhang , Z. Morley Mao

A disruptive technology that is influencing not only computing paradigm but every other business is the rise of big data. Internet of Things (IoT) applications are considered to be a major source of big data. Such IoT applications are in…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-02-23 Xuezhi Zeng , Saurabh Kumar Garg , Peter Strazdins , Prem Jayaraman , Dimitrios Georgakopoulos , Rajiv Ranjan

General trends in computer architecture are shifting more towards parallelism. Multicore architectures have proven to be a major step in processor evolution. With the advancement in multicore architecture, researchers are focusing on…

Hardware Architecture · Computer Science 2019-10-22 Arsalan Shahid , Muhammad Tayyab , Muhammad Yasir Qadri , Nadia N. Qadri , Jameel Ahmed

Advances in sequencing techniques have led to exponential growth in biological data, demanding the development of large-scale bioinformatics experiments. Because these experiments are computation- and data-intensive, they require…

Large Language Models (LLMs) are revolutionizing how users interact with information systems, yet their high inference cost poses serious scalability and sustainability challenges. Caching inference responses, allowing them to be retrieved…

Machine Learning · Computer Science 2026-02-16 Xutong Liu , Baran Atalar , Xiangxiang Dai , Jinhang Zuo , Siwei Wang , John C. S. Lui , Wei Chen , Carlee Joe-Wong

The context window of a large language model is not memory. It is L1 cache: a small, fast, expensive resource that the field treats as the entire memory system. There is no L2, no virtual memory, no paging. Every tool definition, every…

Operating Systems · Computer Science 2026-03-11 Tony Mason

A new class of Second generation high-performance computing applications with heterogeneous, dynamic and data-intensive properties have an extended set of requirements, which cover application deployment, resource allocation, -control, and…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-02-28 Ole Weidner , Malcolm Atkinson , Adam Barker , Rosa Filgueira

Nowadays simulations can produce petabytes of data to be stored in parallel filesystems or large-scale databases. This data is accessed over the course of decades often by thousands of analysts and scientists. However, storing these volumes…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-02-11 Salvatore Di Girolamo , Pirmin Schmid , Thomas Schulthess , Torsten Hoefler
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