English
Related papers

Related papers: Testing Compilers for Programmable Switches Throug…

200 papers

We present Ramulator 2.0, a highly modular and extensible DRAM simulator that enables rapid and agile implementation and evaluation of design changes in the memory controller and DRAM to meet the increasing research effort in improving the…

Hardware Architecture · Computer Science 2023-11-30 Haocong Luo , Yahya Can Tuğrul , F. Nisa Bostancı , Ataberk Olgun , A. Giray Yağlıkçı , Onur Mutlu

Software testing is aimed to improve the delivered reliability of the users. Delivered reliability is the reliability of using the software after it is delivered to the users. Usually the software consists of many modules. Thus, the…

Software Engineering · Computer Science 2017-01-17 Ping Cao , Zhao Dong , Ke Liu , Kai-Yuan Cai

An important aspect of many particle accelerators is the constant evolution and frequent configuration changes that are needed to perform the experiments they are designed for. This often leads to the design of configurable software that…

Debugging CUDA programs has long been challenging because failures often arise from subtle interactions among hardware behavior, compiler decisions, memory hierarchy, and asynchronous execution. More importantly, with the rapid expansion of…

Machine Learning · Computer Science 2026-05-27 Shiyang Li , Haoyang Chen , Mattia Fazzini , Caiwen Ding

High-level synthesis, source-to-source compilers, and various Design Space Exploration techniques for pragma insertion have significantly improved the Quality of Results of generated designs. These tools offer benefits such as reduced…

Software Engineering · Computer Science 2025-03-04 Stéphane Pouget , Louis-Noël Pouchet , Jason Cong

This paper describes a new approach to experimentally estimate the application schedulability for various processor frequencies. We use additional workload generated by an artificial high priority routine to simulate the frequency decrease…

Software Engineering · Computer Science 2007-05-23 Sampsa Fabritius , Raimondas Lencevicius , Edu Metz , Alexander Ran

Scientific machine learning often requires combining known physics with unknown parameters or correction terms learned from data. Existing approaches either ignore known structure, encode it as a soft penalty, or require hand-written…

Machine Learning · Computer Science 2026-05-22 Lucas Sheneman

The usage of Large Language Models (LLMs) for software and test development has continued to increase since LLMs were first introduced, but only recently have the expectations of LLMs become more realistic. Verifying the correctness of code…

Software Engineering · Computer Science 2025-08-20 Zachariah Sollenberger , Rahul Patel , Saieda Ali Zada , Sunita Chandrasekaran

One significant advantage of superconducting processors is their extensive design flexibility, which encompasses various types of qubits and interactions. Given the large number of tunable parameters of a processor, the ability to perform…

Quantum Physics · Physics 2025-04-25 Ziang Wang , Feng Wu , Hui-Hai Zhao , Xin Wan , Xiaotong Ni

RowHammer stands out as a prominent example, potentially the pioneering one, showcasing how a failure mechanism at the circuit level can give rise to a significant and pervasive security vulnerability within systems. Prior research has…

Cryptography and Security · Computer Science 2024-04-30 Ranyang Zhou , Jacqueline T. Liu , Nakul Kochar , Sabbir Ahmed , Adnan Siraj Rakin , Shaahin Angizi

Quantum computers, which take advantage of the superposition and entanglement of physical states, could outperform their classical counterparts in solving problems with technological impact, such as factoring large numbers and searching…

Quantum Physics · Physics 2019-07-30 Yang Wu , Ya Wang , Xi Qin , Xing Rong , Jiangfeng Du

Deterministic execution offers many benefits for debugging, fault tolerance, and security. Running parallel programs deterministically is usually difficult and costly, however - especially if we desire system-enforced determinism, ensuring…

Operating Systems · Computer Science 2010-05-20 Amittai Aviram , Shu-Chun Weng , Sen Hu , Bryan Ford

Initially developed for natural language processing (NLP), Transformers are now widely used for source code processing, due to the format similarity between source code and text. In contrast to natural language, source code is strictly…

Machine Learning · Computer Science 2021-06-25 Nadezhda Chirkova , Sergey Troshin

Hardware heterogeneity is here to stay for high-performance computing. Large-scale systems are currently equipped with multiple GPU accelerators per compute node and are expected to incorporate more specialized hardware in the future. This…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-10-05 Polykarpos Thomadakis , Nikos Chrisochoides

Field Programmable Gate Array (FPGA) logic synthesis compilers (e.g., Vivado, Iverilog, Yosys, and Quartus) are widely applied in Electronic Design Automation (EDA), such as the development of FPGA programs.However, defects (i.e., incorrect…

Hardware Architecture · Computer Science 2024-07-18 Zhihao Xu , Shikai Guo , Guilin Zhao , Peiyu Zou , Xiaochen Li , He Jiang

Tracers provide users with useful information about program executions. In this article, we propose a ``tracer driver''. From a single tracer, it provides a powerful front-end enabling multiple dynamic analysis tools to be easily…

Software Engineering · Computer Science 2008-12-18 Ludovic Langevine , Mireille Ducasse

Prompt engineering has emerged as a powerful technique for guiding large language models (LLMs) toward desired responses, significantly enhancing their performance across diverse tasks. Beyond their role as static predictors, LLMs…

Machine Learning · Computer Science 2025-03-27 Ryumei Nakada , Wenlong Ji , Tianxi Cai , James Zou , Linjun Zhang

The practical realization of quantum programs that require large-scale qubit systems is hindered by current technological limitations. Distributed Quantum Computing (DQC) presents a viable path to scalability by interconnecting multiple…

This paper proposes a hardware-oriented dropout algorithm, which is efficient for field programmable gate array (FPGA) implementation. In deep neural networks (DNNs), overfitting occurs when networks are overtrained and adapt too well to…

Machine Learning · Computer Science 2019-11-15 Yoeng Jye Yeoh , Takashi Morie , Hakaru Tamukoh

Processing-in-memory (PIM) has shown extraordinary potential in accelerating neural networks. To evaluate the performance of PIM accelerators, we present an ISA-based simulation framework including a dedicated ISA targeting neural networks…

Hardware Architecture · Computer Science 2024-02-29 Xinyu Wang , Xiaotian Sun , Yinhe Han , Xiaoming Chen