The terminology used in Per3S for storage includes HPC systems as well as Cloud architectures, the common point between both being scalability. Presentations and talks focus in application, system or architecture. This 10th edition aims to gather during one day researchers from academia and industry, experimented or junior, storage users and customers with the sole purpose to exchange and foster the community.
Per3S is a workshop aiming to bring together the scientific and technological storage community to discuss and address issues and challenges associated to performance and data operations at scale. These topics cover HPC storage as well as Cloud-oriented architectures, both sharing the need for extreme scale.
Per3S fully encourages young researchers to present their work by submitting an abstract. The abstract can relate to an original work, on-going work, with fresh problems/solutions, or one already submitted and/or accepted in an international conference in order to be the subject of discussions.Previous editions of Per3S have successfully fostered a community of researchers both from academia and industry working on storage technologies. The audience is around 50 persons.
The program is organized around 4 sessions: one dedicated to Industrial talks, Storage technologies and data management. In the second session distinguished young researchers present their recent results. Two additional sessions are devoted to academic results from senior researchers. In addition a fourth short session is added to allow students presenting poster to introduce their posters. The posters are displayed and discussed during the buffet.
Each posters is coming with an additional Flash-Presentation. Get within a single day a comprehensive overview of the storage activities in France.
Pers3S workshop spans a full day from 9am to 18h00, with a total of 4 sessions offering the opportunity to meet students, early career researchers, more experiences one and industrial stakeholders.
Fast storage exposes software overhead as a key bottleneck in both direct and buffered I/O. This talk presents UnICom (FAST 2026), which enables efficient direct I/O completion under mixed compute- and I/O-intensive workloads. It then draws on our HotStorage 2026 study to show why small buffered requests are particularly sensitive to software overhead, and to examine the challenges of bringing kernel page-cache benefits to user space.
This presentation analyzes the lifecycle carbon footprint of SSDs versus HDDs for Key-Value stores to determine if SSDs' superior performance offsets their higher manufacturing and energy costs. By measuring hardware power consumption across various workloads, results show that SSDs typically achieve a lower overall carbon footprint due to their high operational energy efficiency. However, HDD-based systems remain the greener choice when SSD capabilities are underutilized or when the data center operates on low-carbon electricity.
Multi-socket NUMA systems struggle with high memory access latencies, particularly in highly parallel, I/O-intensive applications where traditional migration techniques fail. To solve this, we introduce PaCaR, a transparent page cache replication mechanism that duplicates cached pages across nodes while ensuring write consistency and adapting to memory pressure without requiring application changes. Evaluations on a dual-socket server show PaCaR boosts performance by up to 1.4x in synthetic workloads and 25% in real-world applications. This paper received the Best Paper Award during EuroSys 2026
TBA
I/O has been identified as one of the main bottlenecks in HPC. Among the most I/O-intensive operations is checkpointing, which is necessary to save the state of an application and allow it to be restarted at an advanced stage of computation. However, near the parallel file system, concurrency prevents checkpoint phases from reaching the best I/O performance. In this paper, we study I/O interference in this specific context: we look at performance of a checkpoint phase when faced with different interference patterns, exploring aspects such as scale, number of processes, operation, number of files, etc. Through an extensive experimentation, in two systems, we show the impact of these aspects on checkpoint. Moreover, we show that some configurations --- e.g., an application that does random accesses --- lead to degraded system I/O performance.
TBA
Abstract to be provided
This paper is motivated by the observation that edge data intensive applications, in particular AI training, alternate between I/O and compute phases. Notably, we found that processor temperatures consistently decrease during the I/O phases, revealing opportunities to optimize thermal behavior. We propose I/O-Cool, a proactive thermal management strategy for I/O–compute alternating edge workloads that leverages I/Os to maximize cooling opportunities while reducing the need for processor frequency reductions during the compute process
Developing intelligent infrastructure software, high-performance storage systems, and cloud-native solutions for next-generation data centers and accelerated computing
The convergence of High-Performance Computing (HPC) and Artificial Intelligence (AI) demands storage architectures capable of massive throughput, low latency, and robust orchestration. This presentation introduces the VAST AI OS, a next-generation data platform utilizing a Disaggregated and Shared-Everything (DASE) architecture to eliminate data silos and resolve traditional performance-capacity trade-offs. By combining Storage Class Memory (SCM) and QLC flash within a unified multi-protocol namespace, VAST ensures deterministic performance at exabyte scales, optimizes GPU utilization, and seamlessly satisfies the rigorous requirements of modern AI and HPC workloads.
High-performance computing applications rely on parallel file systems, and their I/O performance is strongly affected by configuration parameters such as stripe count. However, the ideal stripe count is highly application- and system-dependent, making it difficult to predict and rarely tuned in practice. As a result, substantial I/O performance potential remains unexplored. We present TOTO, a transparent tool that improves I/O performance without requiring application modifications. TOTO intercepts POSIX calls, characterizes application behavior, and uses a machine learning model to select an appropriate stripe count, even for already opened files. We also introduce an allocation algorithm that balances performance and resource occupation, and describe a methodology for training the model once per system using limited data. Our results show that TOTO can improve I/O performance by up to 4.6 times compared to using a default stripe count, while imposing an overhead of at most 9%. Moreover, compared to the state of the art, TOTO can optimize more applications with a lower resource occupation, which is expected to decrease contention in the I/O infrastructure.
TBA
TBA
TBA
TBA
TBA
Since its inception 10 years ago, Per3S is managed by a steering committee, the committee is fluid and tends to evolve from an edition to the other.
Provided email addresses will only be used to contact participant for logistic purpose or broadcast last minute changes. The emails addresses will not be kept after the Workshop (GDPR).
Click to RegisterThe workshop will be held in Le Couvent des Cordeliers, a historical building from the XVIIth century in the thriving area of Odeon district on the left bank of Paris.
The presentation of last four editions of PER3S are available at the following addresses.