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Increasing model size has unlocked a dazzling array of capabilities in modern language models. At the same time, even frontier models remain vulnerable to jailbreaks and prompt injections, despite concerted efforts to make them robust. As…

Machine Learning · Computer Science 2025-06-06 Nikolaus Howe , Ian McKenzie , Oskar Hollinsworth , Michał Zajac , Tom Tseng , Aaron Tucker , Pierre-Luc Bacon , Adam Gleave

It is commonly agreed that highly parallel software on Exascale computers will suffer from many more runtime failures due to the decreasing trend in the mean time to failures (MTTF). Therefore, it is not surprising that a lot of research is…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-05-19 Faisal Shahzad , Moritz Kreutzer , Thomas Zeiser , Rui Machado , Andreas Pieper , Georg Hager , Gerhard Wellein

Supercomputers become faster as hardware and software technologies continue to evolve. Current supercomputers are capable of 1015 floating point operations per second (FLOPS) that called Petascale system. The High Performance Computer (HPC)…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-09-27 Jalal Abdulbaqi

Exceptions and errors occurring within mission critical applications due to hardware failures have a high cost. With the emerging Next Generation Platforms (NGPs), the rate of hardware failures will likely increase. Therefore, designing our…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-22 Nikunj Gupta , Jackson R. Mayo , Adrian S. Lemoine , Hartmut Kaiser

Exascale systems, expected to emerge by the end of the next decade, will require the exploitation of billion-way parallelism at multiple hierarchical levels in order to achieve the desired sustained performance. The task of assessing future…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-09-27 Matthew Anderson , Maciej Brodowicz , Hartmut Kaiser , Thomas Sterling

Deep reinforcement learning (DRL) has emerged as a powerful paradigm for solving complex decision-making problems. However, DRL-based systems still face significant dependability challenges particularly in real-time environments due to the…

Software Engineering · Computer Science 2026-03-25 Guoxin Su , Thomas Robinson , Hoa Khanh Dam , Li Liu , David S. Rosenblum

We present a new approach to fault tolerance for High Performance Computing system. Our approach is based on a careful adaptation of the Algorithmic Based Fault Tolerance technique (Huang and Abraham, 1984) to the need of parallel…

Distributed, Parallel, and Cluster Computing · Computer Science 2008-06-20 George Bosilca , Remi Delmas , Jack Dongarra , Julien Langou

Due to the diversity and implicit redundancy in terms of processing units and compute kernels, off-the-shelf heterogeneous systems offer the opportunity to detect and tolerate faults during task execution in hardware as well as in software.…

Operating Systems · Computer Science 2014-05-14 Mario Kicherer , Wolfgang Karl

Remote Memory Access (RMA) is an emerging mechanism for programming high-performance computers and datacenters. However, little work exists on resilience schemes for RMA-based applications and systems. In this paper we analyze fault…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-20 Maciej Besta , Torsten Hoefler

This paper proposes a new logic RoCTL* to model robustness in concurrent systems. RoCTL* extends CTL* with the addition of Obligatory and Robustly operators, which quantify over failure-free paths and paths with one more failure…

Logic in Computer Science · Computer Science 2013-09-18 John C. McCabe-Dansted , Tim French , Mark Reynolds , Sophie Pinchinat

Data center hardware refresh cycles are lengthening. However, increasing processor complexity is raising the potential for faults. To achieve longevity in the face of increasingly fault-prone datapaths, fault tolerance is needed, especially…

Hardware Architecture · Computer Science 2025-07-01 Guy Wilks , Brian Li , Jonathan Balkind

Computing at the exascale level is expected to be affected by a significantly higher rate of faults, due to increased component counts as well as power considerations. Therefore, current day numerical algorithms need to be reexamined as to…

Numerical Analysis · Mathematics 2019-05-27 Mark Ainsworth , Christian Glusa

High-level reversible programming languages are few and far between and in general offer only rudimentary abstractions from the details of the underlying machine. Modern programming languages offer a wide array of language constructs and…

Programming Languages · Computer Science 2017-07-26 Tue Haulund

Recent advances in large language models (LLMs) have led to significant progress in robotics, enabling embodied agents to better understand and execute open-ended tasks. However, existing approaches using LLMs face limitations in grounding…

Robotics · Computer Science 2025-04-29 Émiland Garrabé , Pierre Teixeira , Mahdi Khoramshahi , Stéphane Doncieux

Resiliency is the ability of large-scale high-performance computing (HPC) applications to gracefully handle errors, and recover from failures. In this paper, we propose a pattern-based approach to constructing resilience solutions that…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-02-23 Rizwan A. Ashraf , Saurabh Hukerikar , Christian Engelmann

Reversible debuggers help programmers to find the causes of misbehaviours in concurrent programs more quickly, by executing a program backwards from the point where a misbehaviour was observed, and looking for the bug(s) that caused it.…

Programming Languages · Computer Science 2024-08-07 Laura Bocchi , Ivan Lanese , Claudio Antares Mezzina , Shoji Yuen

Whilst there have been great advances in HPC hardware and software in recent years, the languages and models that we use to program these machines have remained much more static. This is not from a lack of effort, but instead by virtue of…

Programming Languages · Computer Science 2016-10-31 Nick Brown

Machine learning (ML) provides us with numerous opportunities, allowing ML systems to adapt to new situations and contexts. At the same time, this adaptability raises uncertainties concerning the run-time product quality or dependability,…

Software Engineering · Computer Science 2022-10-18 Lalli Myllyaho , Mikko Raatikainen , Tomi Männistö , Jukka K. Nurminen , Tommi Mikkonen

This paper addresses the problem of designing LDPC decoders robust to transient errors introduced by a faulty hardware. We assume that the faulty hardware introduces errors during the message passing updates and we propose a general…

Information Theory · Computer Science 2016-11-17 Elsa Dupraz , David Declercq , Bane Vasic , Valentin Savin

Supercomputing systems today often come in the form of large numbers of commodity systems linked together into a computing cluster. These systems, like any distributed system, can have large numbers of independent hardware components…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 Michael Treaster