Deploying AI Frameworks on Secure HPC Systems with Containers

The increasing interest in the usage of Artificial Intelligence techniques (AI) from the research community and industry to tackle "real world" problems, requires High Performance Computing (HPC) resources to efficiently compute and scale complex algorithms across thousands of nodes. Unfortunately, typical data scientists are not familiar with the unique requirements and characteristics of HPC environments. They usually develop their applications with high-level scripting languages or frameworks such as TensorFlow and the installation process often requires connection to external systems to download open source software during the build. HPC environments, on the other hand, are often based on closed source applications that incorporate parallel and distributed computing API's such as MPI and OpenMP, while users have restricted administrator privileges, and face security restrictions such as not allowing access to external systems. In this paper we discuss the issues associated with the deployment of AI frameworks in a secure HPC environment and how we successfully deploy AI frameworks on SuperMUC-NG with Charliecloud.Comment: 6 pages, 2 figures, 2019 IEEE High Performance Extreme Computing Conferenc

The Mont-Blanc Project: First Phase Successfully Finished

Running from October 2011 to June 2015, the aim of the European project Mont-Blanc has been to develop an approach to Exascale computing based on embedded power-efficient technology. The main goals of the project were to i) build an HPC prototype using currently available energy-efficient embedded technology, ii) design a Next Generation system to overcome the limitations of the built prototype and iii) port a set of representative Exascale applications to the system. This article summarises the contributions from the Leibniz Supercomputing Centre (LRZ) and the Juelich Supercomputing Centre (JSC), Germany, to the Mont-Blanc project.Comment: 5 pages, 3 figure

The Mont-Blanc prototype: an alternative approach for high-performance computing systems

High-performance computing (HPC) is recognized as one of the pillars for further advance of science, industry, medicine, and education. Current HPC systems are being developed to overcome emerging challenges in order to reach Exascale level of performance,which is expected by the year 2020. The much larger embedded and mobile market allows for rapid development of IP blocks, and provides more flexibility in designing an application-specific SoC, in turn giving possibility in balancing performance, energy-efficiency and cost. In the Mont-Blanc project, we advocate for HPC systems be built from such commodity IP blocks, currently used in embedded and mobile SoCs. As a first demonstrator of such approach, we present the Mont-Blanc prototype; the first HPC system built with commodity SoCs, memories, and NICs from the embedded and mobile domain, and off-the-shelf HPC networking, storage, cooling and integration solutions. We present the system’s architecture, and evaluation including both performance and energy efficiency. Further, we compare the system’s 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 HPC applications.Postprint (published version

A physical model for the polarized scattering of light

The change in polarization state due to the interaction of light with the surface and beneath the surface of an object has become increasingly important in realistic image synthesis of materials such as metallic, iridescent and pearlescent paint, skin, hair and cosmetics. This paper presents a model for the anisotropic scattering of polarized light based upon the physics of light; which is capable of calculating both partial and complete polarization using a combination of Jones and Mueller calculus, as well as incorporating self shadowing effects. CR Categories and Subject Descriptors: I.3.3 [Computer Graphics]: Three-Dimensional Graphics and Realism – Raytracing;