The fourth International workshop and tutorial on Computational Intelligence on Consumer Games and Graphics Hardware (CIGPU 2011) will be held as a workshop in the GECCO-2011 conference in Dublin 12-16 July 2011. Submissions are invited in (but not limited to) the following areas:
- Parallel genetic programming (GP) on GPU
- Parallel genetic algorithms (GA) on GPU
- Parallel evolutionary programming (EP) on GPU
- Associated or hybrid computational intelligence techniques on GPU
- Particle Swarm Optimisation (PSO)
- Ant colony
- Parallel search algorithms
- Data mining
- Differential Evolution on GPU
- Computational Biology or Bioinformatics on GPU
- Evolutionary computation on video game platforms
- Evolutionary computation on mobile devices
See: http://www.sigevo.org/gecco-2011/workshops.html#cigpu and http://www.cs.ucl.ac.uk/staff/W.Langdon/cigpu/ for more information.
Although trivial background subtraction (BGS) algorithms (e.g. frame differencing, running average…) can perform quite fast, they are not robust enough to be used in various computer vision problems. Some complex algorithms usually give better results, but are too slow to be applied to real-time systems. We propose an improved version of the Extended Gaussian mixture model that utilizes the computational power of Graphics Processing Units (GPUs) to achieve real-time performance. Experiments show that our implementation running on a low-end GeForce 9600GT GPU provides at least 10x speedup. The frame rate is greater than 50 frames per second (fps) for most of the tests, even on HD video formats.
(Vu Pham, Phong Vo, Vu Thanh Hung and Le Hoai Bac: “GPU Implementation of Extended Gaussian Mixture Model for Background Subtraction”. IEEE International Conference on Computing and Communication Technologies, Research, Innovation, and Vision for the Future (RIVF), 2010. [DOI] [code and additional information])
Almost all the presentations from the recent UK GPU Computing Conference held on December 13-14 2010 in Cambridge are now available at http://www.many-core.group.cam.ac.uk/ukgpucc2/programme.shtml. Over 100 delegates saw a varied mix of talks from both industry and academia over the 2 day meeting.
We present a fast GPU-based streaming algorithm to perform collision queries between deformable models. Our approach is based on hierarchical culling and reduces the computation to generating different streams. We present a novel stream registration method to compact the streams and efficiently compute the potentially colliding pairs of primitives. We also use a deferred front tracking method to lower the memory overhead. The overall algorithm has been implemented on different GPUs and we have evaluated its performance on non-rigid and deformable simulations. We highlight our speedups over prior GPU-based and CPU-based algorithms. In practice, our algorithm can perform inter-object and intra-object computations on models composed of hundreds of thousands of triangles in tens of milliseconds.
(Min Tang, Dinesh Manocha, Jiang Lin, Ruofeng Tong, Collision-Streams: “Fast GPU-based Collision Detection for Deformable Models”, in Proceedings of ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games (i3D 2011), San Fransisco, CA, Feb. 18-20, 2011. http://gamma.cs.unc.edu/CSTREAMS)
The MOSIX group announces the release of the MOSIX Virtual OpenCL (VCL) cluster platform version 1.0, which allows OpenCL applications to transparently utilize many GPU devices in clusters. In the VCL run-time environment, all the cluster devices are seen as if they are located in each hosting-node. Applications need not be aware which nodes and devices are available and where the devices are located. VCL benefits OpenCL applications that can use multiple devices concurrently. Read the rest of this entry »
The CPU has traditionally been the computational work horse in scientific computing, but we have seen a tremendous increase in the use of accelerators, such as Graphics Processing Units (GPUs), in the last decade. These architectures are used because they consume less power and offer higher performance than equivalent CPU solutions. They are typically also far less expensive, as more CPUs, and even clusters, are required to match their performance. Even though these accelerators are powerful in terms of floating point operations per second, they are considerably more primitive in terms of capabilities. For example, they cannot even open a file on disk without the use of the CPU. Thus, most applications can benefit from using accelerators to perform heavy computation, whilst running complex tasks on the CPU. This use of different compute resources is often referred to as heterogeneous computing, and we explore the use of heterogeneous architectures for scientific computing in this thesis. Through six papers, we present qualitative and quantitative comparisons of different heterogeneous architectures, the use of GPUs to accelerate linear algebra operations in MATLAB, and efficient shallow water simulation on GPUs. Our results show that the use of heterogeneous architectures can give large performance gains.
(André R. Brodtkorb, “Scientific Computing on Heterogeneous Architectures”, Ph.D. thesis, University of Oslo, Faculty of Mathematics and Natural Sciences, 2010, (PDF))
The “GPUs in Databases” workshop is devoted to sharing the knowledge related to applying GPUs in database environments and to discuss possible future development of this application domain. The workshop topics include, but are not limited to:
- GPU based data compression (lossless/lossy compression and decompression, real time compression and decompression of multimedia)
- GPUs in databases and data warehouses (join processing, data indexing, data aggregation, bulk query processing, analytical query processing)
- Data mining using GPUs (classification, frequent itemsets and association rules, frequent subgraphs, sequential patterns, clustering, social networks mining, regression)
- GPUs in streaming databases (query processing in streaming databases, stream compression/decompression)
- Applications of GPUs in bioinformatics
The workshop will take place on September 19th, 2011 and is co-located with ADBIS 2011 in Vienna, Austria. Submissions are due April 5th, 2011. All of accepted submissions will be published in CEUR workshop proceedings and the best papers will also be published in Lecture Notes in Computer Science and Foundations of Computing and Decision Sciences.
More detailed information can be found at the workshop website http://gid2011.cs.put.poznan.pl.
From a recent announcement:
Calling all software development innovators in general purpose GPU (GPGPU), data parallel and heterogeneous computing. On June 13-16, 2011 AMD will host the AMD Fusion Developer Summit (AFDS) in Bellevue, Washington. The AFDS conference board has issued a call for presentation proposals, inviting creators of next-generation software to share research and development work through presentations based on the latest technical papers or reports.
AFDS will be a great venue for developers, academics and innovative entrepreneurs to network with others engaged in related work, collectively defining the future course of heterogeneous computing. And delivering a presentation offers you the perfect opportunity to advocate programming paradigms or gain support for industry standards.
The submission deadline is Feb. 4 2011, and the full call is available at http://amd-member.com/newsletters/DevCentral/1012.html.
A webinar by Jack Pappas, CEO and Co-Founder of Tidepowerd is being hosted by NVIDIA this coming Wednesday at 9am PST.
Tidepowerd have created GPU.NET, a software tool which allows developers to write GPU-accelerated code in managed languages like C# and VB.NET.
The “Beta 2″ version of GPU.NET, a new product by TidePowerd, has recently been released. It allows developers to write GPU-based code in C# or other .NET-supported languages. GPU.NET beta is available for public download, and the full documentation and several example projects are available online.