Chun-Liang Lee, Yi-Shan Lin, Yaw-Chung Chen
The large quantities of data now being transferred via high-speed networks have made deep packet inspection indispensable for security purposes. Scalable and low-cost signature-based network intrusion detection systems have been developed for deep packet inspection for various software platforms. Traditional approaches that only involve central processing units (CPUs) are now considered inadequate in terms of […]
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Gang Mei
This paper presents a fast implementation of the Graham scan on the GPU. The proposed algorithm is composed of two stages: (1) two rounds of preprocessing performed on the GPU and (2) the finalization of finding the convex hull on the CPU. We first discard the interior points that locate inside a quadrilateral formed by […]
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Xiangyun Hu, Lizhi Ye, Shiyan Pang, Jie Shan
Automatic extraction of ground points, called filtering, is an essential step in producing Digital Terrain Models from airborne LiDAR data. Scene complexity and computational performance are two major problems that should be addressed in filtering, especially when processing large point cloud data with diverse scenes. This paper proposes a fast and intelligent algorithm called Semi-Global […]
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Stefan Westerlund, Christopher Harris
Searching for sources of electromagnetic emission in spectral-line radio astronomy interferometric data is a computationally intensive process. Parallel programming techniques and High Performance Computing hardware may be used to improve the computational performance of a source finding program. However, it is desirable to further reduce the processing time of source finding in order to decrease […]
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Gaurav Chaurasia, Jonathan Ragan-Kelley, Sylvain Paris, George Drettakis, Fredo Durand
Infinite impulse response (IIR) or recursive filters, are essential for image processing because they turn expensive large-footprint convolutions into operations that have a constant cost per pixel regardless of kernel size. However, their recursive nature constrains the order in which pixels can be computed, severely limiting both parallelism within a filter and memory locality across […]
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Tuan Tu Tran, Mathieu Giraud, Jean-Stephane Varre
Seed-based heuristics have proved to be efficient for studying similarity between genetic databases with billions of base pairs. This paper focuses on algorithms and data structures for the filtering phase in seed-based heuristics, with an emphasis on efficient parallel GPU/manycores implementation. We propose a 2-stage index structure which is based on neighborhood indexing and perfect […]
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Lukas Gillsjo
Graphics Processing Units (GPU) and their development tools have advanced recently, and industry has become more interested in using them. Among several development frameworks for GPU(s), OpenCL provides a programming environment to write portable code that can run in parallel. This report describes two case studies of algorithm implementations in OpenCL. The first algorithm is […]
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Dayong Wang, Anil K. Jain
Face retrieval is an enabling technology for many applications, including automatic face annotation, deduplication, and surveillance. In this paper, we propose a face retrieval system which combines a k-NN search procedure with a COTS matcher (PittPatt) in a cascaded manner. In particular, given a query face, we first pre-filter the gallery set and find the […]
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Johannes Koster
The analysis of next-generation sequencing (NGS) data is a major topic in bioinformatics: short reads obtained from DNA, the molecule encoding the genome of living organisms, are processed to provide insight into biological or medical questions. This thesis provides novel solutions to major topics within the analysis of NGS data, focusing on parallelization, scalability and […]
Carter McCardwell, Tuan Dao, Saoni Mukherjee, David Kaeli
OpenCL has become a popular standard to leverage the unique power/performance opportunities found on heterogeneous systems. In this short contribution, we evaluate the latest parallel programming features supported in the OpenCL 2.0 standard. We explore using shared virtual memory and dynamic parallelism to accelerate two example applications.
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Robert W. Senser, Jr.
This dissertation presents our novel declarative framework, called the Declarative Framework for GPUs (DEFG). GPUs are highly sophisticated computing devices, capable of computing at very high speeds. The framework makes the development of OpenCL-based GPU applications less complex, and less time consuming. The framework’s approach is two-fold. First, we developed the DEFG domain-specific language in […]
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Jose Antonio Belloch Rodriguez
Multichannel acoustic signal processing has undergone major development in recent years due to the increased complexity of current audio processing applications. People want to collaborate through communication with the feeling of being together and sharing the same environment, what is considered as Immersive Audio Schemes. In this phenomenon, several acoustic effects are involved: 3D spatial […]
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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.

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Node 1
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  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.3
  • SDK: AMD APP SDK 3.0

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