Publications related to Larrabee (microarchitecture)

Rebooting Virtual Memory with Midgard

Virtual Memory (VM) is a critical programming abstraction that is widely used in various modern computing platforms. With the rise of datacenter computing and birth of planet-scale online services, the semantic and capacity requirements from memory have ev ...

EPFL2023

Massively parallel nodal discontinous Galerkin finite element method simulator for room acoustics

Jan Sickmann Hesthaven

We present a massively parallel and scalable nodal discontinuous Galerkin finite element method (DGFEM) solver for the time-domain linearized acoustic wave equations. The solver is implemented using the libParanumal finite element framework with extensions ...

Sage Publications Ltd2023

Compilation and Design Space Exploration of Dataflow Programs for Heterogeneous CPU-GPU Platforms

Aurélien François Gilbert Bloch

Today's continued increase in demand for processing power, despite the slowdown of Moore's law, has led to an increase in processor count, which has resulted in energy consumption and distribution problems. To address this, there is a growing trend toward ...

EPFL2023

HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics

Anastasia Ailamaki, Syed Mohammad Aunn Raza, Hamish Mcniece Hill Nicholson, Periklis Chrysogelos

Accessing input data is a critical operation in data analytics: i) slow data access significantly degrades performance, and ii) storing everything in the fastest medium, i.e., memory, incurs high operational and hardware costs. Further, while GPUs offer in ...

2023

Determining an optimum quantity of interleaved instruction streams of defined coroutines

Anastasia Ailamaki, Georgios Psaropoulos

A method for optimizing memory access for database operations is provided. The method may include performing a first database operation by at least executing a first instruction stream associated with the first database operation. The first database opera ...

2023

MOD2IR: High-Performance Code Generation for a Biophysically Detailed Neuronal Simulation DSL

Felix Schürmann, Pramod Shivaji Kumbhar, Omar Awile, Snehal Pramod Kumbhar, Ioannis Magkanaris

Advances in computational capabilities and large volumes of experimental data have established computer simulations of brain tissue models as an important pillar in modern neuroscience. Alongside, a variety of domain specific languages (DSLs) have been dev ...

ACM2023

Inter-actions parallel execution on GPU from high-level dataflow synthesis

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

Recent GPU architectures make available numbers of parallel processing units that exceed by orders of magnitude the ones offered by CPU architectures. Whereas programs written using dataflow programming languages are well suited for programming heterogeneo ...

IEEE2022

Practical Byzantine-resilient Stochastic Gradient Descent

Sébastien Louis Alexandre Rouault

Algorithms are everywhere. The recipe for the frangipane cake is an algorithm. If all the listed ingredients are available and the cook is sufficiently deft, after a finite number of small, well-defined steps a delicious dessert will exit the oven. Now, wh ...

EPFL2022

Programming Heterogeneous CPU-GPU Systems by High-Level Dataflow Synthesis

Marco Mattavelli, Endri Bezati, Aurélien François Gilbert Bloch

Heterogeneous processing platforms combining in various architectures CPUs, GPUs, and programmable logic, are continuously evolving providing at each generation higher theoretical levels of computing performance. However, the challenge of how efficiently s ...

IEEE2020

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

Lenstool-HPC: A High Performance Computing based mass modelling tool for cluster-scale gravitational lenses

Jean-Paul Richard Kneib, Christoph Ernst René Schäfer

With the upcoming generation of telescopes, cluster scale strong gravitational lenses will act as an increasingly relevant probe of cosmology and dark matter. The better resolved data produced by current and future facilities requires faster and more effic ...

ELSEVIER2020

A review of CUDA optimization techniques and tools for structured grid computing

Mohammad Khaja Nazeeruddin

Recent advances in GPUs opened a new opportunity in harnessing their computing power for general purpose computing. CUDA, an extension to C programming, is developed for programming NVIDIA GPUs. However, efficiently programming GPUs using CUDA is very tedi ...

2020

Beyond Cameras: Real-Time High-Resolution 3D and Panoramic MultiView Vision Systems with Their Applications

Bilal Demir

The cameras are invented by imitating the human visual system to capture the scene. The camera technologies have been substantially advanced in recent years. 108 MP resolution with 100x hybrid zoom has become standard features for smartphone flagships. In ...

EPFL2020

CoreNEURON : An Optimized Compute Engine for the NEURON Simulator

James Gonzalo King, Felix Schürmann, Michael Lee Hines, Fabien Jonathan Delalondre, Aleksandr Ovcharenko, Pramod Shivaji Kumbhar, 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

GPU-Accelerated Finite Volume Particle Simulation of Free Jet Deviation by Multi-jet Rotating Pelton Runner

Siamak Alimirzazadeh

Numerical simulation of Pelton turbine hydrodynamics is helpful to identify the energy loss mechanisms in the runner and minimize their effect. However, it is a challenging task that involves handling the unsteady free surface flow and moving boundaries re ...

EPFL2019

Recurrent U-Net for Resource-Constrained Segmentation

Pascal Fua, Wei Wang, Mathieu Salzmann, Joachim Ludovic Hugonot, Kaicheng Yu

State-of-the-art segmentation methods rely on very deep networks that are not always easy to train without very large training datasets and tend to be relatively slow to run on standard GPUs. In this paper, we introduce a novel recurrent U-Net architecture ...

IEEE COMPUTER SOC2019

LTRF: Enabling High-Capacity Register Files for GPUs via Hardware/Software Cooperative Register Prefetching

Babak Falsafi, Mario Paulo Drumond Lages De Oliveira, Hamid Sarbazi-Azad, Seyed Borna Ehsani

Graphics Processing Units (GPUs) employ large register files to accommodate all active threads and accelerate context switching. Unfortunately, register files are a scalability bottleneck for future GPUs due to long access latency, high power consumption, ...

2018

An Accelerator for High Efficient Vision Processing

Paolo Ienne, Robert Fasthuber, Zidong Du, Qi Guo

In recent years, neural network accelerators have been shown to achieve both high energy efficiency and high performance for a broad application scope within the important category of recognition and mining applications. Still, both the energy efficiency a ...

Ieee-Inst Electrical Electronics Engineers Inc2017

Improved hybrid/GPU algorithm for solving cardiac electrophysiology problems on Purkinje networks

Alfio Quarteroni, Christian Vergara, Toni Mikael Lassila

Cardiac Purkinje fibers provide an important pathway to the coordinated contraction of the heart. We present a numerical algorithm for the solution of electrophysiology problems across the Purkinje network that is efficient enough to be used in in silico s ...

Wiley2017

Leveraging a Cluster-Booster Architecture for Brain-Scale Simulations

James Gonzalo King, Felix Schürmann, Michael Lee Hines, Pramod Shivaji Kumbhar, Aleksandr Ovcharenko

The European Dynamical Exascale Entry Platform (DEEP) is an example of a new type of heterogeneous supercomputing architecture that include both a standard multicore-based "Cluster" used to run less scalable parts of an application, and an Intel MIC-based ...

Springer Int Publishing Ag2016