Veronica G. Melesse Vergara

The Lustre filesystem serves as a vital element in high-performance parallel storage, meeting the rising demands of scientific, research, and enterprise environments. Widely deployed across HPC environments, ranging from small-scale applications in AI/ML, to domains like oil and gas, drug discovery, and meteorology, and manufacturing, Lustre addresses the universal challenge of efficiently accessing vast and ever-increasing volumes of data. Lustre is the filesystem of choice on six out of the top 10 fastest supercomputers in the world today, over 65% of the top 100, and also for over 60% of the top 500. Despite its widespread popularity, there is a lack of a complete and up-to-date reference, covering Lustre’s evolution, design, and various advancements made over the years. In this journal, we aim to fill this gap by providing a comprehensive journey of Lustre, including its history with significant contributions to HPC, detailed architecture and design elements, exploration of advancements added through its evolution, and future directions. Additionally, we present a comparison of Lustre with other prominent storage technologies of the era. To illustrate the current state of Lustre, we analyze several filesystem trends, including utilization, performance, and usage patterns on Orion, the Lustre filesystem on the first exascale supercomputer Frontier. We hope that this journal serves as a comprehensive educational reference for the current and future generations interested in HPC filesystem storage aspects.

This report highlights significant strides made by Oak Ridge National Laboratory’s Oak Ridge LeadershipComputing Facility (OLCF) in advancing computational research and infrastructure. Through the AdvancedComputing Ecosystem (ACE) strategic initiative, OLCF has been successfully integrated with DOE’sIntegrated Research Infrastructure (IRI) program, establishing itself as a critical framework for enhancingscientific computing capabilities across various domains. This report outlines the activities, accomplishments,and future directions of ACE, emphasizing its role in developing cutting-edge technologies, supportingscience pilots, and fostering collaborations that drive scientific innovation.One of the key achievements of ACE in FY24 has been the establishment of a robust testbed environmentthat facilitates the development and validation of new computing technologies. This testbed, integratedinto the larger IRI ecosystem through Energy Sciences Network (ESnet), allows for seamless collaborationamong DOE’s Advanced Scientific Computing Research (ASCR) facilities, including the Argonne LeadershipComputing Facility (ALCF), the National Energy Research Scientific Computing Center (NERSC), andJefferson Lab (JLab). The testbed has been instrumental in enabling science pilots to experiment withinnovative methodologies in a controlled environment, thereby accelerating the translation of research intopractical applications.ACE has been instrumental in advancing a series of science pilots using computational resources fromOLCF. These pilots span a wide range of scientific domains, from basic energy sciences to biological andenvironmental research, demonstrating the versatility and impact of the ACE framework. By integratingcutting-edge technologies, such as AI-driven analytics and real-time data processing, with HPC, these pilotshave enabled significant advancements in scientific workflows. For instance, projects like LCLStreamand DELERIA have showcased the potential of ACE in optimizing experimental designs, acceleratingdata analysis, and driving innovations that are critical for addressing some of the most complex scientificchallenges of IRI pathfinder projects.ACE has also made significant progress in foundational technology development, particularly in areas suchas data movement, interface design, and scheduling. These advancements have been key in addressingthe complex requirements of modern scientific workflows, ensuring that OLCF remains at the forefront ofhigh-performance computing (HPC). The report details several ongoing projects, including the developmentof the OLCF Facility API, Data Streaming technologies, and the Zambeze distributed orchestration system,which together provide a secure and flexible framework for managing computational resources across adistributed infrastructure.In addition to technical achievements, ACE has played a central role in outreach and engagement activi-ties. Through participation in conferences, hackathons, and training sessions, the ACE team has activelycontributed to the broader scientific community. These efforts have not only facilitated the exchange ofknowledge but have also strengthened collaborations with other DOE facilities and research institutions,further enhancing the impact of the ACE program.Looking ahead, the report outlines strategic plans for FY25, which include continued support for sciencepilots, further integration with ASCR facilities, and the exploration of new technologies. These initiatives aredesigned to ensure that ACE remains a dynamic and adaptable platform, capable of meeting the evolvingneeds of the scientific community. The ongoing collaboration with ORNL’s INTERSECT initiative and theplanned technology refreshes underscore ACE’s commitment to maintaining its leadership in HPC.

Summary: The Oak Ridge Leadership Computing Facility (OLCF) has a long history of supporting and promoting GPU‐accelerated computing starting with the deployment of the Titan supercomputer in 2021 and continuing with the Summit supercomputer which has a theoretical peak performance of approximately 200 petaflops. Because the majority of Summit's computational power comes from its 27,972 GPUs, users must port their applications to one of the supported programming models in order to make efficient use of the system. To prepare the transition to Frontier, the OLCF's exascale supercomputer, users will need to adapt to an entirely new ecosystem which will include new hardware and software technologies. First, users will need to familiarize themselves with the AMD Radeon GPU architecture. Furthermore, users who have been previously relying on CUDA will need to transition to the Heterogeneous‐Computing Interface for Portability (HIP) or one of the other supported programming models (e.g., OpenMP, OpenACC). In this work, we describe our initial experiences and lessons learned in porting three applications or proxy apps currently running on Summit to the HPE/Cray ecosystem to leverage the compute power from AMD GPUs: minisweep, GenASiS, and Sparkler. Each one is representative of current production workloads utilized at the OLCF, different programming languages, and different programming models.