Compared to CPUs, modern GPUs exhibit a high ratio of computing performance per watt, and so current supercomputer designs often include multiple racks of GPUs in order to achieve high teraflop counts at minimal energy cost. GPU programming is thus becoming increasingly important, and yet it remains a challenging task. This paper describes a course […]

November 29, 2015 by hgpu

Quantifying simulation uncertainties is a critical component of rigorous predictive simulation. A key component of this is forward propagation of uncertainties in simulation input data to output quantities of interest. Typical approaches involve repeated sampling of the simulation over the uncertain input data, and can require numerous samples when accurately propagating uncertainties from large numbers […]

November 24, 2015 by hgpu

Accelerators like Intel Xeon Phi aim to fulfill the computational requirements of modern applications. A particular interest to us are those applications that are based on Stencil Computations. Stencils are finite-difference algorithms used in many scientific and engineering applications for solving large-scale and high-dimension partial differential equations. Programmability on massively parallel architectures of such kernels […]

November 11, 2015 by hgpu

To predict the properties of fluid flow over a solid geometry is an important engineering problem. In many applications so-called panel methods (or boundary element methods) have become the standard approach to solve the corresponding partial differential equation. Since panel methods in two dimensions are computationally cheap, they are well suited as the inner solver […]

November 10, 2015 by hgpu

Finite Element Methods (FEM) are ubiquitous in science and engineering where they are used in fields as diverse as structural analysis, ocean modeling and bioengineering. FEM allow us to find approximate solutions to a system of partial differential equations over an unstructured mesh. The first phase of solving a FEM problem, local assembly, involves computing […]

November 3, 2015 by hgpu

In this work we present a multi-level parallel framework for the Optical Flow computation on a GPUs cluster, equipped with a scientific computing middleware (the PetSc library). Starting from a flow-driven isotropic method, which models the optical flow problem through a parabolic partial differential equation (PDE), we have designed a parallel algorithm and its software […]

June 24, 2015 by hgpu

Finite Element Methods are techniques for estimating solutions to boundary value problems for partial differential equations from an approximating subspace. These methods are based on weak or variational forms of the BVP that require less of the problem functions than what the original PDE would suggest in terms of order of differentiability and continuity. In […]

June 7, 2015 by hgpu

This thesis, entitled "High Performance Computing for solving large sparse systems. Optical Diffraction Tomography as a case of study" investigates the computational issues related to the resolution of linear systems of equations which come from the discretization of physical models described by means of Partial Differential Equations (PDEs). These physical models are conceived for the […]

March 30, 2015 by hgpu

In the near future, massively parallel computing systems will be necessary to solve computation intensive applications. The key bottleneck in massively parallel implementation of numerical algorithms is the synchronization of data across processing elements (PEs) after each iteration, which results in significant idle time. Thus, there is a trend towards relaxing the synchronization and adopting […]

March 18, 2015 by hgpu

In this thesis we present the first, to our knowledge, implementation and performance analysis of Hermite methods on GPU accelerated systems. We give analytic background for Hermite methods; give implementations of the Hermite methods on traditional CPU systems as well as on GPUs; give the reader background on basic CUDA programming for GPUs; discuss performance […]

February 2, 2015 by hgpu

In an ideal world, scientific applications are computationally efficient, maintainable and composable and allow scientists to work very productively. We argue that these goals are achievable for a specific application field by choosing suitable domain-specific abstractions that encapsulate domain knowledge with a high degree of expressiveness. This thesis demonstrates the design and composition of domain-specific […]

February 1, 2015 by hgpu

The High Performance Conjugate Gradient (HPCG) benchmark has been recently proposed as a complement to the High Performance Linpack (HPL) benchmark currently used to rank supercomputers in the Top500 list. This new benchmark solves a large sparse linear system using a multigrid preconditioned conjugate gradient (PCG) algorithm. The PCG algorithm contains the computational and communication […]

November 29, 2014 by hgpu