1,817 research outputs found
QCDGPU: open-source package for Monte Carlo lattice simulations on OpenCL-compatible multi-GPU systems
The multi-GPU open-source package QCDGPU for lattice Monte Carlo simulations
of pure SU(N) gluodynamics in external magnetic field at finite temperature and
O(N) model is developed. The code is implemented in OpenCL, tested on AMD and
NVIDIA GPUs, AMD and Intel CPUs and may run on other OpenCL-compatible devices.
The package contains minimal external library dependencies and is OS
platform-independent. It is optimized for heterogeneous computing due to the
possibility of dividing the lattice into non-equivalent parts to hide the
difference in performances of the devices used. QCDGPU has client-server part
for distributed simulations. The package is designed to produce lattice gauge
configurations as well as to analyze previously generated ones. QCDGPU may be
executed in fault-tolerant mode. Monte Carlo procedure core is based on PRNGCL
library for pseudo-random numbers generation on OpenCL-compatible devices,
which contains several most popular pseudo-random number generators.Comment: Presented at the Third International Conference "High Performance
Computing" (HPC-UA 2013), Kyiv, Ukraine; 9 pages, 2 figure
Computational Physics on Graphics Processing Units
The use of graphics processing units for scientific computations is an
emerging strategy that can significantly speed up various different algorithms.
In this review, we discuss advances made in the field of computational physics,
focusing on classical molecular dynamics, and on quantum simulations for
electronic structure calculations using the density functional theory, wave
function techniques, and quantum field theory.Comment: Proceedings of the 11th International Conference, PARA 2012,
Helsinki, Finland, June 10-13, 201
An Experimental Microarchitecture for a Superconducting Quantum Processor
Quantum computers promise to solve certain problems that are intractable for
classical computers, such as factoring large numbers and simulating quantum
systems. To date, research in quantum computer engineering has focused
primarily at opposite ends of the required system stack: devising high-level
programming languages and compilers to describe and optimize quantum
algorithms, and building reliable low-level quantum hardware. Relatively little
attention has been given to using the compiler output to fully control the
operations on experimental quantum processors. Bridging this gap, we propose
and build a prototype of a flexible control microarchitecture supporting
quantum-classical mixed code for a superconducting quantum processor. The
microarchitecture is based on three core elements: (i) a codeword-based event
control scheme, (ii) queue-based precise event timing control, and (iii) a
flexible multilevel instruction decoding mechanism for control. We design a set
of quantum microinstructions that allows flexible control of quantum operations
with precise timing. We demonstrate the microarchitecture and microinstruction
set by performing a standard gate-characterization experiment on a transmon
qubit.Comment: 13 pages including reference. 9 figure
Limits on Fundamental Limits to Computation
An indispensable part of our lives, computing has also become essential to
industries and governments. Steady improvements in computer hardware have been
supported by periodic doubling of transistor densities in integrated circuits
over the last fifty years. Such Moore scaling now requires increasingly heroic
efforts, stimulating research in alternative hardware and stirring controversy.
To help evaluate emerging technologies and enrich our understanding of
integrated-circuit scaling, we review fundamental limits to computation: in
manufacturing, energy, physical space, design and verification effort, and
algorithms. To outline what is achievable in principle and in practice, we
recall how some limits were circumvented, compare loose and tight limits. We
also point out that engineering difficulties encountered by emerging
technologies may indicate yet-unknown limits.Comment: 15 pages, 4 figures, 1 tabl
A GPU-enabled implicit Finite Volume solver for the ideal two-fluid plasma model on unstructured grids
This paper describes the main features of a pioneering unsteady solver for
simulating ideal two-fluid plasmas on unstructured grids, taking profit of
GPGPU (General-purpose computing on graphics processing units). The code, which
has been implemented within the open source COOLFluiD platform, is implicit,
second-order in time and space, relying upon a Finite Volume method for the
spatial discretization and a three-point backward Euler for the time
integration. In particular, the convective fluxes are computed by a multi-fluid
version of the AUSM+up scheme for the plasma equations, in combination with a
modified Rusanov scheme with tunable dissipation for the Maxwell equations.
Source terms are integrated with a one-point rule, using the cell-centered
value. Some critical aspects of the porting to GPU's are discussed, as well as
the performance of two open source linear system solvers (i.e. PETSc,
PARALUTION). The code design allows for computing both flux and source terms on
the GPU along with their Jacobian, giving a noticeable decrease in the
computational time in comparison with the original CPU-based solver. The code
has been tested in a wide range of mesh sizes and in three different systems,
each one with a different GPU. The increased performance (up to 14x) is
demonstrated in two representative 2D benchmarks: propagation of circularly
polarized waves and the more challenging Geospace Environmental Modeling (GEM)
magnetic reconnection challenge.Comment: 22 pages, 7 figure
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