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As inference workloads for large language models (LLMs) scale to meet growing user demand, pipeline parallelism (PP) has become a widely adopted strategy for multi-GPU deployment, particularly in cross-node setups, to improve key-value (KV)…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-06-30 Yongchao He , Bohan Zhao , Zheng Cao

The IceCube experiment has substantial simulation needs and is in continuous search for the most cost-effective ways to satisfy them. The most CPU-intensive part relies on CORSIKA, a cosmic ray air shower simulation. Historically, IceCube…

Performance · Computer Science 2023-08-08 Igor Sfiligoi , David Schultz , Benedikt Riedel , Frank Würthwein

Quantum Hamiltonian simulation is one of the most promising applications of quantum computing and forms the basis for many quantum algorithms. Benchmarking them is an important gauge of progress in quantum computing technology. We present a…

Technological advances in the past decade, hardware and software alike, have made access to high-performance computing (HPC) easier than ever. We review these advances from a statistical computing perspective. Cloud computing makes access…

Computation · Statistics 2021-07-19 Seyoon Ko , Hua Zhou , Jin J. Zhou , Joong-Ho Won

While Large Language Models (LLMs) show significant potential in hardware engineering, current benchmarks suffer from saturation and limited task diversity, failing to reflect LLMs' performance in real industrial workflows. To address this…

Artificial Intelligence · Computer Science 2026-02-03 Zhongkai Yu , Chenyang Zhou , Yichen Lin , Hejia Zhang , Haotian Ye , Junxia Cui , Zaifeng Pan , Jishen Zhao , Yufei Ding

As models become larger, ML accelerators are a scarce resource whose performance must be continually optimized to improve efficiency. Existing performance analysis tools are coarse grained, and fail to capture model performance at the…

Performance · Computer Science 2025-03-20 Ioannis Zarkadas , Amanda Tomlinson , Asaf Cidon , Baris Kasikci , Ofir Weisse

To achieve peak predictive performance, hyperparameter optimization (HPO) is a crucial component of machine learning and its applications. Over the last years, the number of efficient algorithms and tools for HPO grew substantially. At the…

We extend a semantic verification framework for hybrid systems with the Isabelle/HOL proof assistant by an algebraic model for hybrid program stores, a shallow expression model for hybrid programs and their correctness specifications, and…

Logic in Computer Science · Computer Science 2021-06-14 Simon Foster , Jonathan Julián Huerta y Munive , Mario Gleirscher , Georg Struth

We present a formal proof of a time-triggered hardware interface. The design implements the bit-clock synchronization mechanism specified by the FlexRay standard for automotive embedded systems. The design is described at the gate-level. It…

Logic in Computer Science · Computer Science 2011-03-14 Julien Schmaltz

The Isabelle/HOL proof assistant has a powerful library for continuous analysis, which provides the foundation for verification of hybrid systems. However, Isabelle lacks automated proof support for continuous artifacts, which means that…

Logic in Computer Science · Computer Science 2021-02-05 Thomas Hickman , Christian Pardillo Laursen , Simon Foster

Memory performance is often the main bottleneck in modern computing systems. In recent years, researchers have attempted to scale the memory wall by leveraging new technology such as CXL, HBM, and in- and near-memory processing. Developers…

Performance · Computer Science 2024-11-20 Ashwin Poduval , Hayden Coffey , Michael Swift

In recent years, large language models have demonstrated remarkable performance across various natural language processing (NLP) tasks. However, deploying these models for real-world applications often requires efficient inference solutions…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-06-13 Ditto PS , Jithin VG , Adarsh MS

Python's Global Interpreter Lock prevents execution on more than one CPU core at the same time, even when multiple threads are used. However, starting with Python 3.13 an experimental build allows disabling the GIL. While prior work has…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-03-06 José Daniel Montoya Salazar

A systematic understanding of Apple Silicon is lacking in the current landscape of hardware efficiency; research focus is largely centered on accelerating GPUs for large-scale training or inference on CUDA devices. This paper investigates…

Performance · Computer Science 2025-08-13 Afsara Benazir , Felix Xiaozhu Lin

The AIPC concept is gaining popularity, and more and more hybrid CPUs will be running AI models on client devices. However, the current AI inference framework overlooks the imbalanced hardware capability of hybrid CPUs, leading to low…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-12-02 Luo Yu , Liu Yucheng , Shen Haihao

Modern and future processors need to remain functionally correct in the presence of permanent faults to sustain scaling benefits and limit field returns. This paper presents a combined analytical and microarchitectural simulation-based…

Performance · Computer Science 2022-06-24 Panagiota Nikolaou , Yiannakis Sazeides , Maria K. Michael

This is an overview of the Paral-ITP project, which intents to make the proof assistants Isabelle and Coq fit for the multicore era.

ARM-based and x86-64 laptop processors differ not only in instruction-set design, but also in memory hierarchy, core organization, system integration, and power-management mechanisms. This study presents a combined architectural and…

Hardware Architecture · Computer Science 2026-04-22 Mustafa Mert Özyılmaz

Recent advances in probabilistic modelling have led to a large number of simulation-based inference algorithms which do not require numerical evaluation of likelihoods. However, a public benchmark with appropriate performance metrics for…

Machine Learning · Statistics 2021-04-12 Jan-Matthis Lueckmann , Jan Boelts , David S. Greenberg , Pedro J. Gonçalves , Jakob H. Macke

A single-cycle processor completes the execution of an instruction in only one clock cycle. However, its clock period is usually rather long. On the contrary, although clock frequency is higher in a multi-cycle processor, it takes several…

Hardware Architecture · Computer Science 2019-03-04 Ahmad Ahmadi , Reza Faghih Mirzaee
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