Aggregating and Consolidating two High Performant Network Topologies: The ULHPC Experience

in ACM Practice and Experience in Advanced Research Computing (PEARC'22) (2022, July)

High Performance Computing (HPC) encompasses advanced computation over parallel processing. The execution time of a given simulation depends upon many factors, such as the number of CPU/GPU cores, their ... [more ▼]

High Performance Computing (HPC) encompasses advanced computation over parallel processing. The execution time of a given simulation depends upon many factors, such as the number of CPU/GPU cores, their utilisation factor and, of course, the inter- connect performance, efficiency, and scalability. In practice, this last component and the associated topology remains the most significant differentiators between HPC systems and lesser perfor- mant systems. The University of Luxembourg operates since 2007 a large academic HPC facility which remains one of the reference implementation within the country and offers a cutting-edge re- search infrastructure to Luxembourg public research. The main high-bandwidth low-latency network of the operated facility relies on the dominant interconnect technology in the HPC market i.e., Infiniband (IB) over a Fat-tree topology. It is complemented by an Ethernet-based network defined for management tasks, external access and interactions with user’s applications that do not support Infiniband natively. The recent acquisition of a new cutting-edge supercomputer Aion which was federated with the previous flag- ship cluster Iris was the occasion to aggregate and consolidate the two types of networks. This article depicts the architecture and the solutions designed to expand and consolidate the existing networks beyond their seminal capacity limits while keeping at best their Bisection bandwidth. At the IB level, and despite moving from a non-blocking configuration, the proposed approach defines a blocking topology maintaining the previous Fat-Tree height. The leaf connection capacity is more than tripled (moving from 216 to 672 end-points) while exhibiting very marginal penalties, i.e. less than 3% (resp. 0.3%) Read (resp. Write) bandwidth degradation against reference parallel I/O benchmarks, or a stable and sustain- able point-to-point bandwidth efficiency among all possible pairs of nodes (measured above 95.45% for bi-directional streams). With regards the Ethernet network, a novel 2-layer topology aiming for improving the availability, maintainability and scalability of the interconnect is described. It was deployed together with consistent network VLANs and subnets enforcing strict security policies via ACLs defined on the layer 3, offering isolated and secure net- work environments. The implemented approaches are applicable to a broad range of HPC infrastructures and thus may help other HPC centres to consolidate their own interconnect stacks when designing or expanding their network infrastructures. [less ▲]

RESIF 3.0: Toward a Flexible & Automated Management of User Software Environment on HPC facility

in ACM Practice and Experience in Advanced Research Computing (PEARC'21) (2021, July)

High Performance Computing (HPC) is increasingly identified as a strategic asset and enabler to accelerate the research and the business performed in all areas requiring intensive computing and large ... [more ▼]

High Performance Computing (HPC) is increasingly identified as a strategic asset and enabler to accelerate the research and the business performed in all areas requiring intensive computing and large-scale Big Data analytic capabilities. The efficient exploitation of heterogeneous computing resources featuring different processor architectures and generations, coupled with the eventual presence of GPU accelerators, remains a challenge. The University of Luxembourg operates since 2007 a large academic HPC facility which remains one of the reference implementation within the country and offers a cutting-edge research infrastructure to Luxembourg public research. The HPC support team invests a significant amount of time (i.e., several months of effort per year) in providing a software environment optimised for hundreds of users, but the complexity of HPC software was quickly outpacing the capabilities of classical software management tools. Since 2014, our scientific software stack is generated and deployed in an automated and consistent way through the RESIF framework, a wrapper on top of Easybuild and Lmod [5] meant to efficiently handle user software generation. A large code refactoring was performed in 2017 to better handle different software sets and roles across multiple clusters, all piloted through a dedicated control repository. With the advent in 2020 of a new supercomputer featuring a different CPU architecture, and to mitigate the identified limitations of the existing framework, we report in this state-of-practice article RESIF 3.0, the latest iteration of our scientific software management suit now relying on streamline Easybuild. It permitted to reduce by around 90% the number of custom configurations previously enforced by specific Slurm and MPI settings, while sustaining optimised builds coexisting for different dimensions of CPU and GPU architectures. The workflow for contributing back to the Easybuild community was also automated and a current work in progress aims at drastically decrease the building time of a complete software set generation. Overall, most design choices for our wrapper have been motivated by several years of experience in addressing in a flexible and convenient way the heterogeneous needs inherent to an academic environment aiming for research excellence. As the code base is available publicly, and as we wish to transparently report also the pitfalls and difficulties met, this tool may thus help other HPC centres to consolidate their own software management stack. [less ▲]

UL HPC Tutorial: Performance engineering - HPC debugging and profilling

Presentation (2018, June)

UL HPC Tutorial: Advanced Job scheduling with SLURM and OAR

Presentation (2018, June)

UL HPC Tutorial: Basic and Advanced scientific computing using MATLAB

Presentation (2018, June)

UL HPC Tutorial: Bio-informatics workflows and applications

Presentation (2018, June)

UL HPC Tutorial: (Advanced) Prototyping with Python

Presentation (2018, June)

UL HPC Tutorial: Building [custom] software with EasyBuild on the UL HPC platform

Presentation (2018, June)

UL HPC Tutorial: Getting Started on the Uni.lu HPC platform

Presentation (2018, June)

Large-scale research data management: Road to GDPR compliance

Presentation (2018, April)