Related papers: HEPScore: A new CPU benchmark for the WLCG
The ability to collect statistics about the execution of a program within a CPU is of the utmost importance across all fields of computing since it allows characterizing the timing performance of a program. This capability is even more…
We present a comparative analysis of the maximum performance achieved by the Linpack benchmark on compute intensive hardware publicly available from multiple cloud providers. We study both performance within a single compute node, and…
We discuss some specific software engineering challenges in the field of high-performance computing, and argue that the slow adoption of SE tools and techniques is at least in part caused by the fact that these do not address the HPC…
Graphics Processing Units (GPUs) are specialized accelerators in data centers and high-performance computing (HPC) systems, enabling the fast execution of compute-intensive applications, such as Convolutional Neural Networks (CNNs).…
Performance Benchmarking of HPC systems is an ongoing effort that seeks to provide information that will allow for increased performance and improve the job schedulers that manage these systems. We develop a benchmarking tool that utilizes…
In this work, fundamental performance, power, and energy characteristics of the full SPEChpc 2021 benchmark suite are assessed on two different clusters based on Intel Ice Lake and Sapphire Rapids CPUs using the MPI-only codes' variants. We…
High-Performance Computing (HPC) is crucial for performing advanced computational tasks, yet their complexity often challenges users, particularly those unfamiliar with HPC-specific commands and workflows. This paper introduces Hypothetical…
Architectures for quantum computing can only be scaled up when they are accompanied by suitable benchmarking techniques. The document provides a comprehensive overview of the state and recommendations for systematic benchmarking of quantum…
Heterogeneous processors with architecturally different cores (CPU and GPU) integrated on the same die lead to new challenges and opportunities for thermal and power management techniques because of shared thermal/power budgets between…
Benchmarking functionalities in current commercial process mining tools allow organizations to contextualize their process performance through high-level performance indicators, such as completion rate or throughput time. However, they do…
The pace of RISC-V adoption continues to grow rapidly, yet for the successes enjoyed in areas such as embedded computing, RISC-V is yet to gain ubiquity in High Performance Computing (HPC). The Sophon SG2044 is SOPHGO's next generation…
Interest in many-core architectures applied to real time selections is growing in High Energy Physics (HEP) experiments. In this paper we describe performance measurements of many-core devices when applied to a typical HEP online task: the…
Researchers within the Human Brain Project and related projects have in the last couple of years expanded their needs for high-performance computing infrastructures. The needs arise from a diverse set of science challenges that range from…
Synthetic verification techniques such as generating test cases and reward modelling are common ways to enhance the coding capabilities of large language models (LLM) beyond predefined tests. Additionally, code verification has recently…
High energy physics (HEP) experiments at the LHC generate data at a rate of $\mathcal{O}(10)$ Terabits per second. This data rate is expected to exponentially increase as experiments will be upgraded in the future to achieve higher…
Competitive programming has emerged as a critical benchmark for evaluating the reasoning and coding capabilities of Large Language Models (LLMs). Despite impressive progress on existing benchmarks, we argue that current evaluations…
Data processing frameworks are an essential part of HEP experiments' software stacks. Frameworks provide a means by which code developers can undertake the essential tasks of physics data processing, accessing relevant inputs and storing…
We present High-Throughput Hypothesis Evaluation in Description Logic (HT-HEDL). HT-HEDL is a high-performance hypothesis evaluation engine that accelerates hypothesis evaluation computations for inductive logic programming (ILP) learners…
A new generation of manycore processors is on the rise that offers dozens and more cores on a chip and, in a sense, fuses host processor and accelerator. In this paper we target the efficient training of generalized linear models on these…
We recognize the emergence of a statistical computing community focused on working with large computing platforms and producing software and applications that exemplify high-performance statistical computing (HPSC). The statistical…