Publications related to Speedup

lifex-cfd: An open-source computational fluid dynamics solver for cardiovascular applications

Alfio Quarteroni, Luca Dede', Marco Fedele

Computational fluid dynamics (CFD) is an important tool for the simulation of the cardiovascular function and dysfunction. Due to the complexity of the anatomy, the transitional regime of blood flow in the heart, and the strong mutual influence between the ...

Elsevier2023

Full System Exploration of On-Chip Wireless Communication on Many-Core Architectures

David Atienza Alonso, Marina Zapater Sancho, Giovanni Ansaloni, Rafael Medina Morillas, Yasir Mahmood Qureshi, Joshua Alexander Harrison Klein

In order to develop sustainable and more powerful information technology (IT) infrastructures, the challenges posed by the "memory wall" are critical for the design of high-performance and high-efficiency many-core computing systems. In this context, recen ...

IEEE2022

High Performance Computing for gravitational lens modeling: Single vs double precision on GPUs and CPUs

Jean-Paul Richard Kneib, Markus Rexroth, Christoph Ernst René Schäfer

Strong gravitational lensing is a powerful probe of cosmology and the dark matter distribution. Efficient lensing software is already a necessity to fully use its potential and the performance demands will only increase with the upcoming generation of tele ...

ELSEVIER2020

From a week to less than a day: Speedup and scaling of coordinate-scaled exact exchange calculations in plane waves

Ursula Röthlisberger, Martin Peter Bircher

Exact exchange is a primordial ingredient in Kohn–Sham Density Functional Theory based Molecular Dynamics (MD) simulations whenever thermodynamic properties, kinetics, barrier heights or excitation energies have to be predicted with high accuracy. However, ...

2020

Efficient Greedy Coordinate Descent for Composite Problems

Martin Jaggi, Sebastian Urban Stich, Sai Praneeth Reddy Karimireddy, Anastasiia Koloskova

Coordinate descent with random coordinate selection is the current state of the art for many large scale optimization problems. However, greedy selection of the steepest coordinate on smooth problems can yield convergence rates independent of the dimension ...

2019

Stop Crying Over Your Cache Miss Rate: Handling Efficiently Thousands of Outstanding Misses in FPGAs

Paolo Ienne, Mikhail Asiatici

FPGAs rely on massive datapath parallelism to accelerate applications even with a low clock frequency. However, applications such as sparse linear algebra and graph analytics have their throughput limited by irregular accesses to external memory for which ...

ASSOC COMPUTING MACHINERY2019

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

Distributed Learning of CNNs on Heterogeneous CPU/GPU Architectures

José Pedro Rebelo Ferreira Marques, Gabriel Falcao Paiva Fernandes

The convolutional neural networks (CNNs) have proven to be powerful classification tools in tasks that range from check reading to medical diagnosis, reaching close to human perception, and in some cases surpassing it. However, the problems to solve are be ...

TAYLOR & FRANCIS INC2018

eQE: An open-source density functional embedding theory code for the condensed phase

Oliviero Andreussi

In this work, we present the main features and algorithmic details of a novel implementation of the frozen density embedding (FDE) formulation of subsystem density functional theory (DFT) that is specifically designed to enable ab initio molecular dynamics ...

Wiley2017

Reducing circuit design complexity for neuromorphic machine learning systems based on Non-Volatile Memory arrays

Yusuf Leblebici, Alessandro Fumarola

Machine Learning (ML) is an attractive application of Non-Volatile Memory (NVM) arrays [1,2]. However, achieving speedup over GPUs will require minimal neuron circuit sharing and thus highly area-efficient peripheral circuitry, so that ML reads and writes ...

2017

Communication-aware adaptive parareal with application to a nonlinear hyperbolic system of partial dierential equations

Jan Sickmann Hesthaven, Allan Svejstrup Nielsen, Gilles Brunner

In the strong scaling limit, the performance of conventional spatial domain decomposition techniques for the parallel solution of PDEs saturates. When sub-domains become small, halo-communication and other overheard come to dominate. A potential path beyon ...

2017

Near-Memory Address Translation

Babak Falsafi, Javier Picorel Obando, Dorde Jevdic

Memory and logic integration on the same chip is becoming increasingly cost effective, creating the opportunity to offload data-intensive functionality to processing units placed inside memory chips. The introduction of memory-side processing units (MPUs) ...

Ieee2017

Efficient Adaptive Hard Real-time Multi-processor Systems

Stefanos Skalistis

Modern computing systems are based on multi-processor systems, i.e. multiple cores on the same chip. Hard real-time systems are required to perform particular tasks within certain amount of time; failure to do so characterises an unaccepted behavior. Hard ...

EPFL2017

Automatic Generation of Efficient Accelerators for Reconfigurable Hardware

Christos Kozyrakis, Yunqi Zhang

Acceleration in the form of customized datapaths offer large performance and energy improvements over general purpose processors. Reconfigurable fabrics such as FPGAs are gaining popularity for use in implementing application-specific accelerators, thereby ...

Ieee2016

Parallelizing Query Optimization on Shared-Nothing Architectures

Christoph Koch, Immanuel Trummer

Data processing systems offer an ever increasing degree of parallelism on the levels of cores, CPUs, and processing nodes. Query optimization must exploit high degrees of parallelism in order not to gradually become the bottleneck of query evaluation. We s ...

Assoc Computing Machinery2016

Parallel subdomain solver strategies for the algebraic additive Schwarz preconditioner

Simone Deparis, Radu Popescu

Domain-decomposition (DD) methods are used in most, if not all, modern parallel implementations of finite element modeling software. In the solver stage, the algebraic additive Schwarz (AAS) domain-decomposition preconditioner represents a fundamental comp ...

Elsevier Science Bv2016

SIMinG-1k: A thousand-core simulator running on general-purpose graphical processing units

David Atienza Alonso, Luca Benini, Martino Ruggiero, Shivani Raghav

This paper introduces SIMinG-1k-a manycore simulator infrastructure. SIMinG-1k is a graphics processing unit accelerated, parallel simulator for design-space exploration of large-scale manycore systems. It features an optimal trade-off between modeling acc ...

Wiley-Blackwell2013

Querying Persistent Graphs using Solid State Storage

Manoussos Gavriil Athanassoulis

Recent advances in solid state technology have led to the introduction of Solid State Drives (SSDs). Todays SSDs store data persistently using NAND flash memory. While SSDs are more expensive than hard disks when measured in dollars per gigabyte, they are ...

2013

Parallel Preconditioners for Navier-Stokes Equations and Fluid-Structure Interaction Problems : Application to Hemodynamics

Gwenol Grandperrin

The Navier–Stokes equations play a key role in the modeling of blood flows in the vascular sys- tem. The cost for solving the 3D linear system obtained by Finite Element (FE) discretization of the equations, using tetrahedral unstructured meshes and time a ...

EPFL2013

Multiscale Hemodynamics Using GPU Clusters

Efthimios Kaxiras

The parallel implementation of MUPHY, a concurrent multiscale code for large-scale hemodynamic simulations in anatomically realistic geometries, for multi-GPU platforms is presented. Performance tests show excellent results, with a nearly linear parallel s ...

Cambridge University Press2012