Search results for "Parallelism"
showing 10 items of 44 documents
GAPPCO: An Easy to Configure Geometric Algebra Coprocessor Based on GAPP Programs
2017
Because of the high numeric complexity of Geometric Algebra, its use in engineering applications relies heavily on tools and devices for efficient implementations. In this article, we present a novel hardware design for a Geometric Algebra coprocessor, called GAPPCO, which is based on Geometric Algebra Parallelism Programs (GAPP). GAPPCO is a design for a coprocessor combining the advantages of optimizing software with a configurable hardware able to implement arbitrary Geometric Algebra algorithms. The idea is to have a fixed hardware easily and fast to be configured for different algorithms. We describe the new hardware design together with the complete tool chain for its configuration.
Accelerating large-scale biological database search on Xeon Phi-based neo-heterogeneous architectures
2015
In this paper we present new parallelization techniques for searching large-scale biological sequence databases with the Smith-Waterman algorithm on Xeon Phi-based neoheterogenous architectures. In order to make full use of the compute power of both the multi-core CPU and the many-core Xeon Phi hardware, we use a collaborative computing scheme as well as hybrid parallelism. At the CPU side, we employ SSE intrinsics and multi-threading to implement SIMD parallelism. At the Xeon Phi side, we use Knights Corner vector instructions to gain more data parallelism. We have presented two dynamic task distribution schemes (thread level and device level) in order to achieve better load balancing. Fur…
Simulating spin models on GPU
2010
Over the last couple of years it has been realized that the vast computational power of graphics processing units (GPUs) could be harvested for purposes other than the video game industry. This power, which at least nominally exceeds that of current CPUs by large factors, results from the relative simplicity of the GPU architectures as compared to CPUs, combined with a large number of parallel processing units on a single chip. To benefit from this setup for general computing purposes, the problems at hand need to be prepared in a way to profit from the inherent parallelism and hierarchical structure of memory accesses. In this contribution I discuss the performance potential for simulating…
A note on adjusted responses, fitted values and residuals in Generalized Linear Models
2014
Adjusted responses, adjusted fitted values and adjusted residuals are known to play in Generalized Linear Models the role played in Linear Models by observations, fitted values and ordinary residuals. We think this parallelism, which was widely recognized and used in the early literature on Generalized Linear Models, has been somewhat overlooked in more recent presentations. We revise this parallelism, systematizing and proving some results that are either scattered or not satisfactorily spelled out in the literature. In particular, we formally derive the asymptotic dispersion matrix of the (scaled) adjusted residuals, by proving that in Generalized Linear Models the fitted values are asym…
Non linear pseudo-bosons versus hidden Hermiticity. II: The case of unbounded operators
2012
Parallels between the notions of nonlinear pseudobosons and of an apparent non-Hermiticity of observables as shown in paper I (arXiv: 1109.0605) are demonstrated to survive the transition to the quantum models based on the use of unbounded metric in the Hilbert space of states.
Reflections towards a generative theory of musical parallelism
2010
Parallelism plays a core role in Lerdahl and Jackendoff's (1983) GTTM, as it rules the emergence of motivic, metrical, grouping and even formal structures. Due to the high amount of detail and complexity characterising associational structures, neither explicit model nor systematic methodology of parallelism-based structural inference has been included into the GTTM. This paper develops a methodological and computational answer to this problem founded on a computational modelling of pattern extraction operations. The paper focuses in particular on the methodological interest of the pattern mining formalism, and in particular its application to the formalisation of grouping and metrical str…
Empirical Autotuning of Two-level Parallel Linear Algebra Routines on Large cc-NUMA Systems
2012
In large cc-NUMA systems the efficient use of the different levels of the memory hierarchy is not an easy task, and the performance of multithreading implementations of the libraries decreases when the number of cores used increases, so producing an important lost of efficiency. To alleviate this problem, routines with multilevel parallelism can be developed by combining OpenMP and BLAS parallelism. In that way, higher performance can be achieved, but it is necessary to develop some autotuning technique for the appropriate selection of the number of threads to use at each level. The selection can be made through theoretical models of the execution time or some installation methodology. This…
An adaptive method for Volterra–Fredholm integral equations on the half line
2009
AbstractIn this paper we develop a direct quadrature method for solving Volterra–Fredholm integral equations on an unbounded spatial domain. These problems, when related to some important physical and biological phenomena, are characterized by kernels that present variable peaks along space. The method we propose is adaptive in the sense that the number of spatial nodes of the quadrature formula varies with the position of the peaks. The convergence of the method is studied and its performances are illustrated by means of a few significative examples. The parallel algorithm which implements the method and its performances are described.
Improving big-data automotive applications performance through adaptive resource allocation
2019
In automotive applications, connected vehicles (CVs) can collect various information (external temperature, speed, location, etc.) and send them to a central infrastructure for exploitation in a wide range of applications: Eco-Driving, fleet management, environmental monitoring, etc. Such applications are known to generate a massive volume of data that is processed in real or near real time (i.e., data streams) depending on the target application requirements. To handle this data volume, big data architectures, based on stream computing paradigm, are usually adopted. Within this paradigm, data are continuously processed by a set of operators (elementary operations) instances. Further, a str…
Perfect Hashing Structures for Parallel Similarity Searches
2015
International audience; Seed-based heuristics have proved to be efficient for studying similarity between genetic databases with billions of base pairs. This paper focuses on algorithms and data structures for the filtering phase in seed-based heuristics, with an emphasis on efficient parallel GPU/manycores implementa- tion. We propose a 2-stage index structure which is based on neighborhood indexing and perfect hashing techniques. This structure performs a filtering phase over the neighborhood regions around the seeds in constant time and avoid as much as possible random memory accesses and branch divergences. Moreover, it fits particularly well on parallel SIMD processors, because it requ…