11,327 research outputs found
Hierarchical Dynamic Loop Self-Scheduling on Distributed-Memory Systems Using an MPI+MPI Approach
Computationally-intensive loops are the primary source of parallelism in
scientific applications. Such loops are often irregular and a balanced
execution of their loop iterations is critical for achieving high performance.
However, several factors may lead to an imbalanced load execution, such as
problem characteristics, algorithmic, and systemic variations. Dynamic loop
self-scheduling (DLS) techniques are devised to mitigate these factors, and
consequently, improve application performance. On distributed-memory systems,
DLS techniques can be implemented using a hierarchical master-worker execution
model and are, therefore, called hierarchical DLS techniques. These techniques
self-schedule loop iterations at two levels of hardware parallelism: across and
within compute nodes. Hybrid programming approaches that combine the message
passing interface (MPI) with open multi-processing (OpenMP) dominate the
implementation of hierarchical DLS techniques. The MPI-3 standard includes the
feature of sharing memory regions among MPI processes. This feature introduced
the MPI+MPI approach that simplifies the implementation of parallel scientific
applications. The present work designs and implements hierarchical DLS
techniques by exploiting the MPI+MPI approach. Four well-known DLS techniques
are considered in the evaluation proposed herein. The results indicate certain
performance advantages of the proposed approach compared to the hybrid
MPI+OpenMP approach
A Taxonomy of Workflow Management Systems for Grid Computing
With the advent of Grid and application technologies, scientists and
engineers are building more and more complex applications to manage and process
large data sets, and execute scientific experiments on distributed resources.
Such application scenarios require means for composing and executing complex
workflows. Therefore, many efforts have been made towards the development of
workflow management systems for Grid computing. In this paper, we propose a
taxonomy that characterizes and classifies various approaches for building and
executing workflows on Grids. We also survey several representative Grid
workflow systems developed by various projects world-wide to demonstrate the
comprehensiveness of the taxonomy. The taxonomy not only highlights the design
and engineering similarities and differences of state-of-the-art in Grid
workflow systems, but also identifies the areas that need further research.Comment: 29 pages, 15 figure
A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks
In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs
A Parallel Adaptive P3M code with Hierarchical Particle Reordering
We discuss the design and implementation of HYDRA_OMP a parallel
implementation of the Smoothed Particle Hydrodynamics-Adaptive P3M (SPH-AP3M)
code HYDRA. The code is designed primarily for conducting cosmological
hydrodynamic simulations and is written in Fortran77+OpenMP. A number of
optimizations for RISC processors and SMP-NUMA architectures have been
implemented, the most important optimization being hierarchical reordering of
particles within chaining cells, which greatly improves data locality thereby
removing the cache misses typically associated with linked lists. Parallel
scaling is good, with a minimum parallel scaling of 73% achieved on 32 nodes
for a variety of modern SMP architectures. We give performance data in terms of
the number of particle updates per second, which is a more useful performance
metric than raw MFlops. A basic version of the code will be made available to
the community in the near future.Comment: 34 pages, 12 figures, accepted for publication in Computer Physics
Communication
Dynamic Loop Scheduling Using MPI Passive-Target Remote Memory Access
Scientific applications often contain large computationally-intensive
parallel loops. Loop scheduling techniques aim to achieve load balanced
executions of such applications. For distributed-memory systems, existing
dynamic loop scheduling (DLS) libraries are typically MPI-based, and employ a
master-worker execution model to assign variably-sized chunks of loop
iterations. The master-worker execution model may adversely impact performance
due to the master-level contention. This work proposes a distributed
chunk-calculation approach that does not require the master-worker execution
scheme. Moreover, it considers the novel features in the latest MPI standards,
such as passive-target remote memory access, shared-memory window creation, and
atomic read-modify-write operations. To evaluate the proposed approach, five
well-known DLS techniques, two applications, and two heterogeneous hardware
setups have been considered. The DLS techniques implemented using the proposed
approach outperformed their counterparts implemented using the traditional
master-worker execution model
SKIRT: hybrid parallelization of radiative transfer simulations
We describe the design, implementation and performance of the new hybrid
parallelization scheme in our Monte Carlo radiative transfer code SKIRT, which
has been used extensively for modeling the continuum radiation of dusty
astrophysical systems including late-type galaxies and dusty tori. The hybrid
scheme combines distributed memory parallelization, using the standard Message
Passing Interface (MPI) to communicate between processes, and shared memory
parallelization, providing multiple execution threads within each process to
avoid duplication of data structures. The synchronization between multiple
threads is accomplished through atomic operations without high-level locking
(also called lock-free programming). This improves the scaling behavior of the
code and substantially simplifies the implementation of the hybrid scheme. The
result is an extremely flexible solution that adjusts to the number of
available nodes, processors and memory, and consequently performs well on a
wide variety of computing architectures.Comment: 21 pages, 20 figure
Density Functional Theory calculation on many-cores hybrid CPU-GPU architectures
The implementation of a full electronic structure calculation code on a
hybrid parallel architecture with Graphic Processing Units (GPU) is presented.
The code which is on the basis of our implementation is a GNU-GPL code based on
Daubechies wavelets. It shows very good performances, systematic convergence
properties and an excellent efficiency on parallel computers. Our GPU-based
acceleration fully preserves all these properties. In particular, the code is
able to run on many cores which may or may not have a GPU associated. It is
thus able to run on parallel and massive parallel hybrid environment, also with
a non-homogeneous ratio CPU/GPU. With double precision calculations, we may
achieve considerable speedup, between a factor of 20 for some operations and a
factor of 6 for the whole DFT code.Comment: 14 pages, 8 figure
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