Programming
Tags: Algorithms, Astrophysics, Cosmology and Extragalactic Astrophysics, Galaxy Astrophysics, GPU cluster, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, nVidia GeForce 9800 GX2
Tags: Astrophysics, ATI, ATI IL, ATI Radeon HD 5870, Computational Complexity, Computer science, Galaxy Astrophysics, Instrumentation and Methods for Astrophysics, KD-tree, OpenCL, Optimization, Performance
Tags: Astrophysics, Galaxy Astrophysics, High Energy Astrophysical Phenomena, nVidia, OpenCL, Plasma physics
Tags: Astrophysics, CUDA, FFT, Galaxy Astrophysics, Instrumentation and Methods for Astrophysics, nVidia, Physics, Tesla C1060
Tags: Computer science, Galaxy Astrophysics, N-body simulation, Networking and Internet Architecture, nVidia, nVidia GeForce 8800 Ultra
Tags: Astrophysics, Celestial mechanics, Galaxy Astrophysics, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, OpenMP, Stellar dynamics, Tesla C1060
Tags: Astrophysics, Black hole physics, Galaxy Astrophysics, Gravitational waves, High Energy Astrophysical Phenomena, N-body simulation, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280, nVidia GeForce GTX 285, Solar and Stellar Astrophysics, Stellar dynamics
Tags: Astrophysics, Galaxy Astrophysics, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, Package, Tesla C1060
Tags: Astrophysics, Galaxy Astrophysics, Globular clusters, GPU cluster, N-body simulation, nVidia, nVidia GeForce GTX 280
Tags: Astrophysics, Cosmology and Extragalactic Astrophysics, CUDA, Earth and Planetary Astrophysics, Galaxy Astrophysics, General Relativity and Quantum Cosmology, High Energy Astrophysical Phenomena, Instrumentation and Methods for Astrophysics, nVidia, Physics, Solar and Stellar Astrophysics, Tesla S1070
Tags: Astrophysics, ATI, ATI CAL, ATI Radeon HD 4850, ATI Radeon HD 4870, ATI Stream, Galaxy Astrophysics, Instrumentation and Methods for Astrophysics, RV770
Tags: Astrophysics, ATI, ATI IL, ATI Stream, Galaxy Astrophysics, Instrumentation and Methods for Astrophysics, RV770
Most viewed papers (last 30 days)
- Graphics Programming on the Web WebCL Course Notes
- Simulating the universe with GPU-accelerated supercomputers: n-body methods, tests, and examples
- Secrets from the GPU
- Implementations of the FFT algorithm on GPU
- Fluid Motion Modelling Using Vortex Particle Method on GPU
- Adding GPU Computing to Computer Organization Courses
- libWater: Heterogeneous Distributed Computing Made Easy
- Fast Implementation of Scale Invariant Feature Transform Based on CUDA
- Faster Upper Body Pose Estimation and Recognition Using CUDA
- Analyzing Locality of Memory References in GPU Architectures
Rating
Optimizing a Biomedical Imaging Orientation Score Framework
Graphics Programming on the Web WebCL Course Notes
Adaptive Dynamic Load Balancing in Heterogeneous Multiple GPUs-CPUs Distributed Setting: Case Study of B&B Tree Search
Duality based optical flow algorithms with applications
In-Place Recursive Approach for All-Pairs Shortest Paths Problem Using OpenCL
A parallel decoding algorithm of LDPC codes using CUDA
Optimizing MapReduce for GPUs with effective shared memory usage
OpenCL parallel Processing using General Purpose Graphical Processing units - TiViPE software development
Kernelet: High-Throughput GPU Kernel Executions with Dynamic Slicing and Scheduling
Stencil-Aware GPU Optimization of Iterative Solvers
Recent source codes
Events
October 1-4, 2013 Lyon, France The 2013 International Workshop on Embedded Multicore Systems, ICPP-EMS 2013 |
November 13-15, 2013 Zhangjiajie, China 3rd International Workshop on Embedded Multi-core Computing and Applications, EMCA 2013 |
February 2-6, 2014 San Francisco, USA |
February 12-14, 2014 Turin, Italy |
November 11-14, 2013 San Jose, California, USA |
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
- 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
- HDD: 2TB, Raid-0
- OS: OpenSUSE 11.4
- SDK: AMD APP SDK 2.8
- 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
- HDD: 2TB, Raid-0
- OS: OpenSUSE 12.2
- SDK: nVidia CUDA Toolkit 5.0.35, AMD APP SDK 2.8
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.
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