The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Graphics Processing Units (GPUs) have been widely used as accelerators in large-scale heterogeneous computing systems. However, current programming models can only support the utilization of local GPUs. When using non-local GPUs, programmers need to explicitly call API functions for data communication across computing nodes. As such, programming GPUs in large-scale computing systems is more challenging...
In this paper, we propose an efficient implementation of the branch and bound method for knapsack problems on a CPU-GPU system via CUDA. Branch and bound computations can be carried out either on the CPU or on a GPU according to the size of the branch and bound list. A better management of GPUs memories, less GPUCPU communications and better synchronization between GPU threads are proposed in this...
In the last few years, Graphics Processing Units (GPUs) have become a great tool for massively parallel computing. GPUs are specifically designed for throughput and face several design challenges, specially what is known as the Power and Memory Walls. In these devices, available resources should be used to enhance performance and throughput, as the performance per watt is really high. For massively...
Unprecedented production of short reads from the new high-throughput sequencers has posed challenges to align short reads to reference genomes with high sensitivity and high speed. Many CPU-based short read aligners have been developed to address this challenge. Among them, one popular approach is the seed-and-extend heuristic. For this heuristic, the first and foremost step is to generate seeds between...
We present an automated symbolic verifier for checking the functional correctness of GPGPU kernels parametrically, for an arbitrary number of threads. Our tool checks the functional equivalence of a kernel and its optimized versions, helping debug errors introduced during memory coalescing and bank conflict elimination related optimizations. Key features of our work include: (1) a symbolic method...
Genetic Algorithms (GAs) are powerful search techniques. However when they are applied to complex problems, they consume large computation power. One of the choices to make them faster is to use a parallel implementation. This paper presents a parallel implementation of Combinatorial Optimisation with Coincidence Algorithm (COIN) on Graphic Processing Units. COIN is a modern GA. It has a wide range...
This paper elaborates on a new, fresh parallel optimization algorithm specially engineered to run on Graphic Processing Units (GPUs). The underlying operation relates to Systolic Computation. The algorithm, called Systolic Genetic Search (SGS) is based on the synchronous circulation of solutions through a grid of processing units and tries to profit from the parallel architecture of GPUs. The proposed...
A direct communication facility, called DCFA, for a many-core based cluster, whose compute node consists of many-core units connected to the host via PCI Express with Infiniband, is designed and evaluated. Because a many-core unit is a device of the PCI Express bus, it is not capable of configuring and initializing the Infiniband HCA, according to the PCI Express specification. This means that the...
Modern computer systems are becoming increasingly heterogeneous by comprising multi-core CPUs, GPUs, and other accelerators. Current programming approaches for such systems usually require the application developer to use a combination of several programming models (e.g., MPI with OpenCL or CUDA) in order to exploit the full compute capability of a system. In this paper, we presentd OpenCL (Distributed...
Intensity model with blur effects are widely employed to accurately simulate the imaging process of a star simulator used for attitude determination and guiding feedback. The model is computationally intensive and the time requirements are proportional to the number of stars in the simulation, imposing great demands of computing power for realistic uses. This paper presents two star simulators using...
We detail the design and experiences in delivering a specialty multicore computing course whose materials are openly available. The course ambitiously covers three multicore programming paradigms: shared memory (OpenMP), device (CUDA) and message passing (RCCE), and involves significant practical work on their respective platforms: an UltraSPARC T2, Fermi GPU and the Intel Single-Chip Cloud Computer...
Due to the exponentially growing bioinformatics databases and rapidly popular of GPU for general purpose computing, it is promising to employ GPU techniques to accelerate the sequence search process. Hmmsearch from HMMER bioinformatics software package is a wildly used software tool for sensitive profile HMM (Hidden Markov Model) searches of biological sequence databases. In this paper, we implement...
Due to their outstanding computational performance, many acceleration devices, such as GPUs, the Cell Broadband Engine (Cell/B.E.), and multi-core computing are attracting a lot of attention in the field of high-performance computing. Although there are many programming models and languages de-signed for programming accelerators, such as CUDA, AMD Accelerated Parallel Processing (AMD APP), and OpenCL,...
Overlapping computations and communication is a key to accelerating stencil applications on parallel computers, especially for GPU clusters. However, such programming is a time-consuming part of the stencil application development. To address this problem, we developed an automatic code generation tool to produce a parallel stencil application with latency hiding automatically from its dataflow model...
To cope with the complexity of programming GPU accelerators for medical imaging computations, we developed a framework to describe image processing kernels in a domain-specific language, which is embedded into C++. The description uses decoupled access/execute metadata, which allow the programmer to specify both execution constraints and memory access patterns of kernels. A source-to-source compiler...
K-Means is the clustering algorithm which is widely used in many areas such as information retrieval, computer vision and pattern recognition. With the recent advance in General Purpose Graphics Processing Unit (GPGPU), we can use a modern GPU which is capable to do computation up to Tflops to calculate K-Means clustering on average problems. However, due to the exponential growth of data, the K-Means...
Application programming for GPUs (Graphics Processing Units) is complex and error-prone, because the popular approaches - CUDA and OpenCL - are intrinsically low-level and offer no special support for systems consisting of multiple GPUs. The SkelCL library presented in this paper is built on top of the OpenCL standard and offers pre-implemented recurring computation and communication patterns (skeletons)...
In recent years, there has been what can only be described as an explosion in the types of processing devices one can expect to find within a given computer system. These include the multi-core CPU, the General Purpose Graphics Processing Unit (GPGPU) and the Accelerated Processing Unit (APU), to name but a few. The widespread uptake of these systems presents would-be users with at least two problems...
In order to obtain more accurate solutions of polynomial systems with numerical continuation methods we use multiprecision arithmetic. Our goal is to offset the overhead of double double arithmetic accelerating the path trackers and in particular Newton's method with a general purpose graphics processing unit. In this paper we describe algorithms for the massively parallel evaluation and differentiation...
We implemented and evaluated the triple precision Basic Linear Algebra Subprograms (BLAS) subroutines, AXPY, GEMV and GEMM on a Tesla C2050. In this paper, we present a Double Single (D+S) type triple precision floating-point value format and operations. They are based on techniques similar to Double-Double (DD) type quadruple precision operations. On the GPU, the D+S-type operations are more costly...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.