arXiv subjects

Maksymilian Graczyk

Publications and source records attributed to Maksymilian Graczyk.

3 recordsLinked to original sources

arXiv2025

Enabling Heterogeneous Performance Analysis for Scientific Workloads

Heterogeneous computing integrates diverse processing elements, such as CPUs, GPUs, and FPGAs, within a single system, aiming to leverage the strengths of each architecture to optimize performance and energy consumption. In this context, efficient performance analysis plays a critical role in determining the most suitable platform for dispatching tasks, ensuring that workloads are allocated to the processing units where they can execute most effectively. Adaptyst is a novel ongoing effort at CERN, with the aim to develop an open-source, architecture-agnostic performance analysis for scientific workloads. This study explores the performance and implementation complexity of two built-in eBPF-based methods such as Uprobes and USDT, with the aim of outlining a roadmap for future integration into Adaptyst and advancing toward heterogeneous performance analysis capabilities.

cs.PF↗

arXiv2025

Enhancing software-hardware co-design for HEP by low-overhead profiling of single- and multi-threaded programs on diverse architectures with Adaptyst

Given the recent technological trends and novel computing paradigms spanning both software and hardware, physicists and software developers can no longer just rely on computers becoming faster to meet the ever-increasing computing demands of their research. Adapting systems to the new environment may be difficult though, especially in case of large and complex applications. Therefore, we introduce Adaptyst (formerly AdaptivePerf): an open-source and architecture-agnostic tool aiming for making these computational and procurement challenges easier to address. At the moment, Adaptyst profiles on- and off-CPU activity of codes, traces all threads and processes spawned by them, and analyses low-level software-hardware interactions to the extent supported by hardware. The tool addresses the main shortcomings of Linux "perf" and has been successfully tested on x86-64, arm64, and RISC-V instruction set architectures. Adaptyst is planned to be evolved towards a software-hardware co-design framework which scales from embedded to high-performance computing in both legacy and new applications and takes into account a bigger picture than merely choosing between CPUs and GPUs. Our paper describes the current development of the project and its roadmap.

cs.PF↗

arXiv2021

Autoencoders on FPGAs for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider

In this paper, we show how to adapt and deploy anomaly detection algorithms based on deep autoencoders, for the unsupervised detection of new physics signatures in the extremely challenging environment of a real-time event selection system at the Large Hadron Collider (LHC). We demonstrate that new physics signatures can be enhanced by three orders of magnitude, while staying within the strict latency and resource constraints of a typical LHC event filtering system. This would allow for collecting datasets potentially enriched with high-purity contributions from new physics processes. Through per-layer, highly parallel implementations of network layers, support for autoencoder-specific losses on FPGAs and latent space based inference, we demonstrate that anomaly detection can be performed in as little as $80\,$ns using less than 3% of the logic resources in the Xilinx Virtex VU9P FPGA. Opening the way to real-life applications of this idea during the next data-taking campaign of the LHC.

physics.ins-det↗