Apr, 12

Power analysis and optimizations for GPU architecture using a power simulator

As one of the most popular many-core architecture, GPUs have illustrated power in many non-graphic applications. Traditional general purpose computing systems tend to integrate GPU as the co-processor to accelerate parallel computing tasks. Meanwhile, GPUs also result in high power consumption, which accounts for a large proportion of the total system power consumption. In this […]
Apr, 12

CUDA Memory Optimizations for Large Data-Structures in the Gravit Simulator

Modern GPUs open a completely new field to optimize embarrassingly parallel algorithms. Implementing an algorithm on a GPU confronts the programmer with a new set of challenges for program optimization. Some of the most notable ones are isolating the part of the algorithm that can be optimized to run on the GPU; tuning the program […]
Apr, 12

Automated development of applications for graphical processing units using rewriting rules

Recently there was an active development of parallel programming methods concerning implementation of general-purpose algorithms on graphical processing units (GPUs). Using this specialized hardware allows increasing performance significantly, but requires low-level programming and understanding details of underlying hardware and software platform. Therefore there is a need for automating development process. This paper presents a technique […]
Apr, 12

Stream-Centric Stereo Matching and View Synthesis: A High-Speed Approach on GPUs

In this paper, we propose a real-time image-based rendering (IBR) system. It is specifically designed for photorealistic view synthesis at high-speed on the graphics processing unit (GPU). We steer the proposed IBR system design with two high-level ideas. First, for cost-effective IBR, as long as the synthesized views look visually plausible, the estimated disparity and […]
Apr, 12

An Analytical Approach to the Design of Parallel Block Cipher Encryption/Decryption: A CPU/GPU Case Study

GPUs are at the fore-front of a radical transformation that is taking place in software design. The ability to process multiple data streams simultaneously is delivering substantial benefits to a large collection of domains. Depending on the application, these benefits can be expanded by utilizing the not-insignificant power of traditional CPUs. Multi-core CPUs with a […]
Apr, 12

GPU Accelerated Path-Planning for Multi-agents in Virtual Environments

Many games are populated by synthetic humanoid actors that act as autonomous agents. The animation of humanoids in real-time applications is yet a challenge if the problem involves attaining a precise location in a virtual world (path-planning), and moving realistically according to its own personality, intentions and mood (motion planning). In this paper we present […]
Apr, 12

The fast evaluation of hidden Markov models on GPU

It is compute-intensive to evaluate the probability of an observation sequence on a hidden Markov model. Some fast algorithms exit, the forward-backward procedure is the most popular one among them. The forward-backward procedure can save much computation, but its time complexity is N^2T, in other words, there is a high computational complexity in the algorithm. […]
Apr, 12

Accelerating System-Level Design Tasks Using Commodity Graphics Hardware: A Case Study

Many system-level design tasks (e.g. timing analysis, hardware/software partitioning and design space exploration) involve computational kernels that are intractable (usually NP-hard). As a result, they involve high running times even for mid-sized problems. In this paper we explore the possibility of using commodity graphics processing units (GPUs) to accelerate such tasks that commonly arise in […]
Apr, 12

Simulating Spiking Neural P systems without delays using GPUs

We present in this paper our work regarding simulating a type of P system known as a spiking neural P system (SNP system) using graphics processing units (GPUs). GPUs, because of their architectural optimization for parallel computations, are well-suited for highly parallelizable problems. Due to the advent of general purpose GPU computing in recent years, […]
Apr, 11

Interactive Simulation and Visualization of Fluids with Surface Raycasting

We present a method to couple particle-based fluid simulation methods such as Smoothed Particle Hydrodynamics (SPH) and volume rendering in order to visualize the fluid. A volume is generated from the fluid’s implicit density field so volume raycasting can be performed to render the surface on the GPU. The volume generation algorithm is also implemented […]
Apr, 11

Real-time 3-D object recognition using scale invariant feature transform and stereo vision

Scale invariant feature transform (SIFT) and stereo vision are applied together to recognize objects in real time. This work reports the performance of a GPU (graphic processing unit) based real-time feature detector in capturing the features of 3D objects when the objects undergo rotational and translational motions in cluttered backgrounds. We have compared the performance […]
Apr, 11

EXOCHI: architecture and programming environment for a heterogeneous multi-core multithreaded system

Future mainstream microprocessors will likely integrate specialized accelerators, such as GPUs, onto a single die to achieve better performance and power efficiency. However, it remains a keen challenge to program such a heterogeneous multicore platform, since these specialized accelerators feature ISAs and functionality that are significantly different from the general purpose CPU cores. In this […]
Page 574 of 762« First...102030...572573574575576...580590600...Last »

* * *

* * *

Like us on Facebook

HGPU group

169 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1276 peoples are following HGPU @twitter

* * *

Free GPU computing nodes at hgpu.org

Registered users can now run their OpenCL application at hgpu.org. We provide 1 minute of computer time per each run on two nodes with two AMD and one nVidia graphics processing units, correspondingly. There are no restrictions on the number of starts.

The platforms are

Node 1
  • GPU device 0: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • GPU device 1: AMD/ATI Radeon HD 6970 2GB, 880MHz
  • CPU: AMD Phenom II X6 @ 2.8GHz 1055T
  • RAM: 12GB
  • OS: OpenSUSE 13.1
  • SDK: AMD APP SDK 2.9
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: nVidia GeForce GTX 560 Ti 2GB, 822MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.2
  • SDK: nVidia CUDA Toolkit 6.0.1, AMD APP SDK 2.9

Completed OpenCL project should be uploaded via User dashboard (see instructions and example there), compilation and execution terminal output logs will be provided to the user.

The information send to hgpu.org will be treated according to our Privacy Policy

HGPU group © 2010-2014 hgpu.org

All rights belong to the respective authors

Contact us: