10,012 research outputs found
Exponential Integrators on Graphic Processing Units
In this paper we revisit stencil methods on GPUs in the context of
exponential integrators. We further discuss boundary conditions, in the same
context, and show that simple boundary conditions (for example, homogeneous
Dirichlet or homogeneous Neumann boundary conditions) do not affect the
performance if implemented directly into the CUDA kernel. In addition, we show
that stencil methods with position-dependent coefficients can be implemented
efficiently as well.
As an application, we discuss the implementation of exponential integrators
for different classes of problems in a single and multi GPU setup (up to 4
GPUs). We further show that for stencil based methods such parallelization can
be done very efficiently, while for some unstructured matrices the
parallelization to multiple GPUs is severely limited by the throughput of the
PCIe bus.Comment: To appear in: Proceedings of the 2013 International Conference on
High Performance Computing Simulation (HPCS 2013), IEEE (2013
BriskStream: Scaling Data Stream Processing on Shared-Memory Multicore Architectures
We introduce BriskStream, an in-memory data stream processing system (DSPSs)
specifically designed for modern shared-memory multicore architectures.
BriskStream's key contribution is an execution plan optimization paradigm,
namely RLAS, which takes relative-location (i.e., NUMA distance) of each pair
of producer-consumer operators into consideration. We propose a branch and
bound based approach with three heuristics to resolve the resulting nontrivial
optimization problem. The experimental evaluations demonstrate that BriskStream
yields much higher throughput and better scalability than existing DSPSs on
multi-core architectures when processing different types of workloads.Comment: To appear in SIGMOD'1
A Parallel Mesh-Adaptive Framework for Hyperbolic Conservation Laws
We report on the development of a computational framework for the parallel,
mesh-adaptive solution of systems of hyperbolic conservation laws like the
time-dependent Euler equations in compressible gas dynamics or
Magneto-Hydrodynamics (MHD) and similar models in plasma physics. Local mesh
refinement is realized by the recursive bisection of grid blocks along each
spatial dimension, implemented numerical schemes include standard
finite-differences as well as shock-capturing central schemes, both in
connection with Runge-Kutta type integrators. Parallel execution is achieved
through a configurable hybrid of POSIX-multi-threading and MPI-distribution
with dynamic load balancing. One- two- and three-dimensional test computations
for the Euler equations have been carried out and show good parallel scaling
behavior. The Racoon framework is currently used to study the formation of
singularities in plasmas and fluids.Comment: late submissio
Quantum Monte Carlo for large chemical systems: Implementing efficient strategies for petascale platforms and beyond
Various strategies to implement efficiently QMC simulations for large
chemical systems are presented. These include: i.) the introduction of an
efficient algorithm to calculate the computationally expensive Slater matrices.
This novel scheme is based on the use of the highly localized character of
atomic Gaussian basis functions (not the molecular orbitals as usually done),
ii.) the possibility of keeping the memory footprint minimal, iii.) the
important enhancement of single-core performance when efficient optimization
tools are employed, and iv.) the definition of a universal, dynamic,
fault-tolerant, and load-balanced computational framework adapted to all kinds
of computational platforms (massively parallel machines, clusters, or
distributed grids). These strategies have been implemented in the QMC=Chem code
developed at Toulouse and illustrated with numerical applications on small
peptides of increasing sizes (158, 434, 1056 and 1731 electrons). Using 10k-80k
computing cores of the Curie machine (GENCI-TGCC-CEA, France) QMC=Chem has been
shown to be capable of running at the petascale level, thus demonstrating that
for this machine a large part of the peak performance can be achieved.
Implementation of large-scale QMC simulations for future exascale platforms
with a comparable level of efficiency is expected to be feasible
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