Dirk Brömmel

The mont-blanc prototype: an alternative approach for HPC systems

High-performance computing (HPC) is recognized as one of the pillars for further progress in science, industry, medicine, and education. Current HPC systems are being developed to overcome emerging architectural challenges in order to reach Exascale level of performance, projected for the year 2020. The much larger embedded and mobile market allows for rapid development of intellectual property (IP) blocks and provides more flexibility in designing an application-specific system-on-chip (SoC), in turn providing the possibility in balancing performance, energy-efficiency, and cost. In the Mont-Blanc project, we advocate for HPC systems being built from such commodity IP blocks, currently used in embedded and mobile SoCs. As a first demonstrator of such an approach, we present the Mont-Blanc prototype; the first HPC system built with commodity SoCs, memories, and network interface cards (NICs) from the embedded and mobile domain, and off-the-shelf HPC networking, storage, cooling, and integration solutions. We present the systems architecture and evaluate both performance and energy efficiency. Further, we compare the systems abilities against a production level supercomputer. At the end, we discuss parallel scalability and estimate the maximum scalability point of this approach across a set of applications.

Extreme-scaling Applications 24/7 on JUQUEEN Blue Gene/Q

Julich Supercomputing Centre has offered Extreme Scaling Workshops since 2009, with the latest edition in February 2015 giving seven international code teams an opportunity to (im)prove the scaling of their applications to all 458 752 cores of the JUQUEEN IBM Blue Gene/Q. Each of them successfully adapted their application codes and datasets to the restricted compute-node memory and exploit the massive parallelism with up to 1.8 million processes or threads. They thereby qualified to become members of the High-Q Club which now has over 24 codes demonstrating extreme scalability. Achievements in both strong and weak scaling are compared, and complemented with a review of program languages and parallelisation paradigms, exploitation of hardware threads, and file I/O requirements.

GPU-Accelerated Particle-in-Cell Code on Minsky

Particle-in-cell (PIC) methods are widely used on today’s supercomputers. In this paper we consider JuSPIC, an application for which good scaling properties could be demonstrated on a 6PFlop/s BlueGene/Q system. We report on efforts to port this application to emerging supercomputing architectures based on IBM POWER processors and NVIDIA graphics processing units.

Extreme-scaling applications en route to exascale

Feedback from the previous years very successful workshop motivated the organisation of a three-day workshop from 1 to 3 February 2016, during which the 28-rack JUQUEEN BlueGene/Q system with 458 752 cores was reserved for over 50 hours. Eight international code teams were selected to use this opportunity to investigate and improve their application scalability, assisted by staff from JSC Simulation Laboratories and Cross-Sectional Teams. Ultimately seven teams had codes successfully run on the full JUQUEEN system. Strong scalability demonstrated by Code_Saturne and Seven-League Hydro, both using 4 OpenMP threads for 16 MPI processes on each compute node for a total of 1 835 008 threads, qualify them for High-Q Club membership. Existing members CIAO and iFETI were able to show that they had additional solvers which also scaled acceptably. Furthermore, large-scale in-situ interactive visualisation was demonstrated with a CIAO simulation using 458 752 MPI processes running on 28 racks coupled via JUSITU to VisIt. The two adaptive mesh refinement utilities, ICI and p4est, showed that they could respectively scale to run with 458 752 and 971 504 MPI ranks, but both encountered problems loading large meshes. Parallel file I/O issues also hindered large-scale executions of PFLOTRAN. Poor performance of a NEST-import module which loaded and connected 1.9 TiB of neuron and synapse data was tracked down to an internal data-structure mismatch with the HDF5 file objects that prevented use of MPI collective file reading, which when rectified is expected to enable large-scale neuronal network simulations. Comparative analysis is provided to the 25 codes in the High-Q Club at the start of 2016, which includes five codes that qualified from the previous workshop. Despite more mixed results, we learnt more about application file I/O limitations and inefficiencies which continue to be the primary inhibitor to large-scale simulations.