Concept

Blue Gene (superordinateur)

Publications associées (26)

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A 16-bit Floating-Point Near-SRAM Architecture for Low-power Sparse Matrix-Vector Multiplication

David Atienza Alonso, Giovanni Ansaloni, Grégoire Axel Eggermann, Marco Antonio Rios

State-of-the-art Artificial Intelligence (AI) algorithms, such as graph neural networks and recommendation systems, require floating-point computation of very large matrix multiplications over sparse data. Their execution in resource-constrained scenarios, ...

2023

Fast Parallel Algorithms for Enumeration of Simple, Temporal, and Hop-constrained Cycles

Paolo Ienne, Kubilay Atasu, Jovan Blanusa

Cycles are one of the fundamental subgraph patterns and being able to enumerate them in graphs enables important applications in a wide variety of fields, including finance, biology, chemistry, and network science. However, to enable cycle enumeration in r ...

New York2023

Biomolecular Simulation: a Perspective from High Performance Computing

Ursula Röthlisberger, Viacheslav Bolnykh, Paolo Carloni

High-Performance Computing is impacting on all biomedical sciences, including molecular biophysics. Here, we describe general parallel computing strategies (multi-threading and distributed computing) used in all the natural sciences, including molecular bi ...

WILEY-V C H VERLAG GMBH2020

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GPUs are becoming increasingly popular in large scale data center installations due to their strong, embarrassingly parallel, processing capabilities. Data management systems are riding the wave by using GPUs to accelerate query execution, mainly for analy ...

2020

CoreNEURON : An Optimized Compute Engine for the NEURON Simulator

Felix Schürmann, James Gonzalo King, Michael Lee Hines, Pramod Shivaji Kumbhar, Aleksandr Ovcharenko, Jérémy Pierre Benoit Fouriaux

The NEURON simulator has been developed over the past three decades and is widely used by neuroscientists to model the electrical activity of neuronal networks. Large network simulation projects using NEURON have supercomputer allocations that individually ...

2019

A Minimally Intrusive Low-Memory Approach to Resilience for Existing Transient Solvers

Allan Svejstrup Nielsen

We propose a novel, minimally intrusive approach to adding fault tolerance to existing complex scientific simulation codes, used for addressing a broad range of time-dependent problems on the next generation of supercomputers. Exascale systems have the pot ...

2019

Fully-Asynchronous Cache-Efficient Simulation of Detailed Neural Networks

Felix Schürmann, Michael Lee Hines

Modern asynchronous runtime systems allow the re-thinking of large-scale scientific applications. With the example of a simulator of morphologically detailed neural networks, we show how detaching from the commonly used bulk-synchronous parallel (BSP) exec ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

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Modern supercomputer architectures are evolving towards embedding more and more cores per compute node, often making use of accelerators such as GPUs, in which thousands of threads can be executed concurrently. To make legacy codes profit efficiently from ...

2018

Scaling and Resilience in Numerical Algorithms for Exascale Computing

Allan Svejstrup Nielsen

The first Petascale supercomputer, the IBM Roadrunner, went online in 2008. Ten years later, the community is now looking ahead to a new generation of Exascale machines. During the decade that has passed, several hundred Petascale capable machines have bee ...

EPFL2018

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Portability and efficiency are usually antagonists in multi-core computing. In order to develop efficient code, one needs to take into account the topology of the target multi-cores (e.g., for locality). This clearly hampers code portability. In this paper ...

ACM Press2017