Posts
Dec, 15
Analysis and Optimization Techniques for Massively Parallel Processors
In response to the ever growing demand for computing power, heterogeneous parallelism has emerged as a widespread computing paradigm in the past decade or so. In particular, massively parallel processors such as graphics processing units (GPUs) have become the prevalent throughput computing elements in heterogeneous systems, offering high performance and power efficiency for general-purpose workloads. […]
Dec, 15
Easy-to-Use On-the-Fly Binary Program Acceleration on Many-Cores
This paper introduces Binary Acceleration At Runtime (BAAR), an easy-to-use on-the-fly binary acceleration mechanism which aims to tackle the problem of enabling existent software to automatically utilize accelerators at runtime. BAAR is based on the LLVM Compiler Infrastructure and has a client-server architecture. The client runs the program to be accelerated in an environment which […]
Dec, 15
Performance Comparison of GPUs with a Genetic Algorithm based on CUDA
Generally genetic algorithm (GA) has disadvantage of taking a lot of computation time, and it is worth reducing the execution time while keeping good quality and result. Comparative experiments are conducted with one CPU and four GPUs using CUDA (Compute Unified Device Architecture) and generational GA. We implement the fitness functions of the GA which […]
Dec, 15
Bamboo: Automatic Translation of MPI Source into a Latency-Tolerant Form
Communication remains a significant barrier to scalability on distributed-memory systems. At present, the trend in architectural system design, which focuses on enhancing node performance, exacerbates the communication problem, since the relative cost of communication grows as the computation rate increases. This problem will be more pronounced at the exascale, where computational rates will be orders […]
Dec, 14
Heuristics for Conversion Process of GPU’s Kernels for Multiples Kernels with Concurrent Optimization Divergence
Graphics Processing Units have been created with the objective of accelerating the construction and processing of graphic images. In its historical evolution line, concerned with the large computational capacity inherent, these devices started to be used for general purposes. However, the design of the GPUs don’t work well with divergent algorithms, mainly conditionals and repetitions. […]
Dec, 14
Locality-Aware Automatic Parallelization for GPGPU with OpenHMPP Directives
The use of GPUs for general purpose computation has increased dramatically in the past years due to the rising demands of computing power and their tremendous computing capacity at low cost. Hence, new programming models have been developed to integrate these accelerators with high-level programming languages, giving place to heterogeneous computing systems. Unfortunately, this heterogeneity […]
Dec, 14
Acceleration of Hessenberg Reduction for Nonsymmetric Matrix
The worth of finding a general solution for nonsymmetric eigenvalue problems is specified in many areas of engineering and science computations, such as reducing noise to have a quiet ride in automotive industrial engineering or calculating the natural frequency of a bridge in civil engineering. The main objective of this thesis is to design a […]
Dec, 14
Graph Processing on GPU
Graph mining and data management has become a significant area because more and more new applications to various data mining problems in social networking, computational biology, chemical data analysis and drug discovery are emerging recently. Although traditional mining methods have been extended to process graphs, many graph applications still confront huge challenges due to continuous […]
Dec, 13
C++ AMP: Accelerated Massive Parallelism with Microsoft Visual C++
Capitalize on the faster GPU processors in today’s computers with the C++ AMP code library—and bring massive parallelism to your project. With this practical book, experienced C++ developers will learn parallel programming fundamentals with C++ AMP through detailed examples, code snippets, and case studies. Learn the advantages of parallelism and get best practices for harnessing […]
Dec, 12
Real-Time Grasp Detection Using Convolutional Neural Networks
We present an accurate, real-time approach to robotic grasp detection based on convolutional neural networks. Our network performs single-stage regression to graspable bounding boxes without using standard sliding window or region proposal techniques. The model outperforms state-of-the-art approaches by 14 percentage points and runs at 13 frames per second on a GPU. Our network can […]
Dec, 12
A Survey Paper on Solving TSP using Ant Colony Optimization on GPU
Ant Colony Optimization (ACO) is meta-heuristic algorithm inspired from nature to solve many combinatorial optimization problem such as Travelling Salesman Problem (TSP). There are many versions of ACO used to solve TSP like, Ant System, Elitist Ant System, Max-Min Ant System, Rank based Ant System algorithm. For improved performance, these methods can be implemented in […]
Dec, 12
cuLGT: Lattice Gauge Fixing on GPUs
We adopt CUDA-capable Graphic Processing Units (GPUs) for Landau, Coulomb and maximally Abelian gauge fixing in 3+1 dimensional SU(3) and SU(2) lattice gauge field theories. A combination of simulated annealing and overrelaxation is used to aim for the global maximum of the gauge functional. We use a fine grained degree of parallelism to achieve the […]