Single instruction multiple data

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Génie informatique
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Parallélisme (informatique)

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Publications associées (31)

An Optimizing Multi-platform Source-to-source Compiler Framework for the NEURON MODeling Language

Felix Schürmann, James Gonzalo King, Michael Lee Hines, Pramod Shivaji Kumbhar, Omar Awile, Jorge Blanco Alonso, Liam Roger George Keegan

Domain-specific languages (DSLs) play an increasingly important role in the generation of high performing software. They allow the user to exploit domain knowledge for the generation of more efficient code on target architectures. Here, we describe a new c ...

Springer2020

BLADE: A BitLine Accelerator for Devices on the Edge

David Atienza Alonso, Marina Zapater Sancho, Alexandre Sébastien Julien Levisse, William Andrew Simon, Yasir Mahmood Qureshi

The increasing ubiquity of edge devices in the consumer market, along with their ever more computationally expensive workloads, necessitate corresponding increases in computing power to support such workloads. In-memory computing is attractive in edge devi ...

2019

Exploiting Flow Graph of System of ODEs to Accelerate the Simulation of Biologically-Detailed Neural Networks

Felix Schürmann, Michael Lee Hines, Bruno Ricardo Da Cunha Magalhães

Exposing parallelism in scientific applications has become a core requirement for efficiently running on modern distributed multicore SIMD compute architectures. The granularity of parallelism that can be attained is a key determinant for the achievable ac ...

IEEE2019

Asynchronous Branch-Paralle Simulation of Detailed Neuron Models

Felix Schürmann, Michael Lee Hines

Simulations of electrical activity of networks of morphologically detailed neuron models allow for a better understanding of the brain. State-of-the-art simulations describe the dynamics of ionic currents and biochemical processes within branching topologi ...

2019

Asynchronous Simulation of Neuronal Activity

Bruno Ricardo Da Cunha Magalhães

Simulations of the electrical activity of networks of morphologically-detailed neuron models allow for a better understanding of the brain. Short time to solution is critical in order to study long biological processes such as synaptic plasticity and learn ...

EPFL2019

Extreme Scalability of DFT-Based QM/MM MD Simulations Using MiMiC

Ursula Röthlisberger, Simone Meloni, Martin Peter Bircher, Viacheslav Bolnykh, Jógvan Magnus Olsen, Paolo Carloni

We present a highly scalable DFT-based QM/MM implementation developed within MiMiC, a recently introduced multiscale modeling framework that uses a loose-coupling strategy in conjunction with a multiple-program multiple-data (MPMD) approach. The computatio ...

2019

Linebacker: Preserving Victim Cache Lines in Idle Register Files of GPUs

Yunho Oh

Modern GPUs suffer from cache contention due to the limited cache size that is shared across tens of concurrently running warps. To increase the per-warp cache size prior techniques proposed warp throttling which limits the number of active warps. Warp thr ...

ASSOC COMPUTING MACHINERY2019

Design of approximate and precision-scalable circuits for embedded multimedia and neural-network processing

Vincent Frédéric Camus

Density, speed and energy efficiency of integrated circuits have been increasing exponentially for the last four decades following Moore's law. However, power and reliability pose several challenges to the future of technology scaling. Approximate computin ...

EPFL2019

MiMiC: A Novel Framework for Multiscale Modeling in Computational Chemistry

Ursula Röthlisberger, Simone Meloni, Martin Peter Bircher, Viacheslav Bolnykh, Paolo Carloni

We present a flexible and efficient framework for multiscale modeling in computational chemistry (MiMiC). It is based on a multiple-program multiple-data (MPMD) model with loosely coupled programs. Fast data exchange between programs is achieved through th ...

AMER CHEMICAL SOC2019

RPCValet: NI-Driven Tail-Aware Balancing of µs-Scale RPCs

Babak Falsafi, Alexandros Daglis, Mark Johnathon Sutherland

Modern online services come with stringent quality requirements in terms of response time tail latency. Because of their decomposition into fine-grained communicating software layers, a single user request fans out into a plethora of short, μs-scale RPCs, ...

ACM2019

Low-Overhead Dynamic Instruction Mix Generation using Hybrid Basic Block Profiling

Willy Zwaenepoel, Andrzej Pawel Nowak

Dynamic instruction mixes form an important part of the toolkits of performance tuners, compiler writers, and CPU architects. Instruction mixes are traditionally generated using software instrumentation, an accurate yet slow method, that is normally limite ...

2018

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