Parallel Unsmoothed Aggregation Algebraic Multigrid Algorithms on GPUs

We design and implement a parallel algebraic multigrid method for isotropic graph Laplacian problems on multicore Graphical Processing Units (GPUs). The proposed AMG method is based on the aggregation framework. The setup phase of the algorithm uses a parallel maximal independent set algorithm in forming aggregates and the resulting coarse level hierarchy is then used in a K-cycle iteration solve phase with a $\ell^1$-Jacobi smoother. Numerical tests of a parallel implementation of the method for graphics processors are presented to demonstrate its effectiveness.Comment: 18 pages, 3 figure

Resiliency in numerical algorithm design for extreme scale simulations

This work is based on the seminar titled ‘Resiliency in Numerical Algorithm Design for Extreme Scale Simulations’ held March 1–6, 2020, at Schloss Dagstuhl, that was attended by all the authors. Advanced supercomputing is characterized by very high computation speeds at the cost of involving an enormous amount of resources and costs. A typical large-scale computation running for 48 h on a system consuming 20 MW, as predicted for exascale systems, would consume a million kWh, corresponding to about 100k Euro in energy cost for executing 1023 floating-point operations. It is clearly unacceptable to lose the whole computation if any of the several million parallel processes fails during the execution. Moreover, if a single operation suffers from a bit-flip error, should the whole computation be declared invalid? What about the notion of reproducibility itself: should this core paradigm of science be revised and refined for results that are obtained by large-scale simulation? Naive versions of conventional resilience techniques will not scale to the exascale regime: with a main memory footprint of tens of Petabytes, synchronously writing checkpoint data all the way to background storage at frequent intervals will create intolerable overheads in runtime and energy consumption. Forecasts show that the mean time between failures could be lower than the time to recover from such a checkpoint, so that large calculations at scale might not make any progress if robust alternatives are not investigated. More advanced resilience techniques must be devised. The key may lie in exploiting both advanced system features as well as specific application knowledge. Research will face two essential questions: (1) what are the reliability requirements for a particular computation and (2) how do we best design the algorithms and software to meet these requirements? While the analysis of use cases can help understand the particular reliability requirements, the construction of remedies is currently wide open. One avenue would be to refine and improve on system- or application-level checkpointing and rollback strategies in the case an error is detected. Developers might use fault notification interfaces and flexible runtime systems to respond to node failures in an application-dependent fashion. Novel numerical algorithms or more stochastic computational approaches may be required to meet accuracy requirements in the face of undetectable soft errors. These ideas constituted an essential topic of the seminar. The goal of this Dagstuhl Seminar was to bring together a diverse group of scientists with expertise in exascale computing to discuss novel ways to make applications resilient against detected and undetected faults. In particular, participants explored the role that algorithms and applications play in the holistic approach needed to tackle this challenge. This article gathers a broad range of perspectives on the role of algorithms, applications and systems in achieving resilience for extreme scale simulations. The ultimate goal is to spark novel ideas and encourage the development of concrete solutions for achieving such resilience holistically

Acrylic room thermometer inscribed "Hon. John Glenn"

Acrylic room thermometer inscribed "Hon. John Glenn" from the "IEEE [Institute of Electrical and Electronics Engineers] 1982 Conference on United States Technology Policy, February 24-25, 1982."Artifact Size: 3.5H by 3.5W by 1D.Credit: John Glenn Archives, The Ohio State University

EPR Techniques to Probe Insertion and Conformation of Spin-Labeled Proteins in Lipid Bilayers

Electron paramagnetic resonance (EPR) spectroscopy of spin-labeled membrane proteins is a valuable biophysical technique to study structural details and conformational transitions of proteins close to their physiological environment, for example, in liposomes, membrane bilayers, and nanodiscs. Unlike in nuclear magnetic resonance (NMR) spectroscopy, having only one or few specific side chains labeled at a time with paramagnetic probes makes the size of the object under investigation irrelevant in terms of technique sensitivity. As a drawback, extensive site-directed mutagenesis is required in order to analyze the properties of the protein under investigation. EPR can provide detailed information on side chain dynamics of large membrane proteins or protein complexes embedded in membranes with an exquisite sensitivity for flexible regions and on water accessibility profiles across the membrane bilayer. Moreover, distances between the two spin-labeled side chains in membrane proteins can be detected with high precision at cryogenic temperatures. The application of EPR to membrane proteins still presents some challenges in terms of sample preparation, sensitivity and data interpretation, thus it is difficult to give ready-to-go methodological recipes. However, new technological developments (arbitrary waveform generators) and new spin labels spectroscopically orthogonal to nitroxides increased the range of applicability from in vitro toward in-cell EPR experiments. This chapter is an updated version of the one published in the first edition of the book and describes the state of the art in the application of nitroxide-based site-directed spin labeling EPR to membrane proteins, addressing new tools such as arbitrary waveform generators and spectroscopically orthogonal labels, such as Gd(III)-based labels. We will present challenges in sample preparation and data analysis for functional and structural membrane protein studies using site-directed spin labeling techniques and give experimental details on EPR techniques providing information on side chain dynamics and water accessibility using nitroxide probes. An updated optimal Q-band DEER setup for nitroxide probes will be described, and its extension to gadolinium-containing samples will be addressed.</p

A survey of general-purpose computation on graphics hardware

The rapid increase in the performance of graphics hardware, coupled with recent improvements in its programmability, have made graphics hardware acompelling platform for computationally demanding tasks in awide variety of application domains. In this report, we describe, summarize, and analyze the latest research in mapping general-purpose computation to graphics hardware. We begin with the technical motivations that underlie general-purpose computation on graphics processors (GPGPU) and describe the hardware and software developments that have led to the recent interest in this field. We then aim the main body of this report at two separate audiences. First, we describe the techniques used in mapping general-purpose computation to graphics hardware. We believe these techniques will be generally useful for researchers who plan to develop the next generation of GPGPU algorithms and techniques. Second, we survey and categorize the latest developments in general-purpose application development on graphics hardware