high performance computing on graphics processing units: hgpu.org

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 […]

Graph algorithms are used in several domains such as social networking, biological sciences, computational geometry, and compilers, to name a few. It has been shown that they possess enough parallelism to keep several computing resources busy – even hundreds of cores on a GPU. Unfortunately, tuning their implementation for efficient execution on a particular hardware […]

Sparse matrix-vector multiplication (SpMV) is a widely used kernel in scientific applications as well as data analytics. Many GPU implementations of SpMV have been proposed, proposing different sparse matrix representations. However, no sparse matrix representation is consistently superior, and the best representation varies for sparse matrices with different sparsity patterns. In this paper we study […]

This master’s thesis concerns the implementation of a GPUaccelerated version of Mehrotra’s predictor-corrector interior point algorithm for large-scale linear programming (LP). The implementations are tested on LP problems arising in the financial industry, where there is high demand for faster LP solvers. The algorithm was implemented in C++, MATLAB and CUDA, using double precision for […]

Parallelization is the answer to the ever-growing demands of computing power by taking advantage of multi-core processor technology and modern many-core graphics compute units. Multi-core CPUs and many-core GPUs have the potential to substantially reduce the execution time of a program but it is often a challenging task to ensure that all available hardware is […]

Embedded languages are often compiled at application runtime; thus, embedded compile-time errors become application runtime errors. We argue that advanced type system features, such as GADTs and type families, play a crucial role in minimising such runtime errors. Specifically, a rigorous type discipline reduces runtime errors due to bugs in both embedded language applications and […]

Sparse matrix-vector multiplication (SpMV) is a core kernel in numerous applications, ranging from physics simulation and large-scale solvers to data analytics. Many GPU implementations of SpMV have been proposed, targeting several sparse representations and aiming at maximizing overall performance. No single sparse matrix representation is uniformly superior, and the best performing representation varies for sparse […]

Modern video compression algorithms put significant strain on a system’s CPU, especially for video encoding. The ever increasing demands for using video compression algorithms in a wide range of applications necessitate the use of processing components that boost the speed and quality of the video compression algorithm’s execution. The vast parallel computational capabilities of modern […]

Interactions between surfaces and proteins occur in many vital processes and are crucial in biotechnology: the ability to control specific interactions is essential in fields like biomaterials, biomedical implants and biosensors. In the latter case, biosensor sensitivity hinges on ligand proteins adsorbing on bioactive surfaces with a favorable orientation, exposing reaction sites to target molecules. […]

We provide an efficient implementation of existing parameter synthesis techniques for stochastic systems modelled as continuous-time Markov chains (CTMCs). These techniques iteratively decompose the parameter space into its subspaces and approximate the satisfaction function that for any parameter values from the parameter space returns the probability of the formula being satisfied in the CTMC given […]

We propose a two stage visual matching pipeline including a first step using VLAD signatures for filtering results, and a second step which reranks the top results using raw matching of SIFT descriptors. This enables adjusting the tradeoff between high computational cost of matching local descriptors and the insufficient accuracy of compact signatures in many […]

Graphics processing units (GPUs) are highly parallel processors that are now commonly used in the acceleration of a wide range of computationally intensive tasks. GPU programs often suffer from data races and deadlocks, necessitating systematic testing. Conventional GPU debuggers are ineffective at finding and root-causing races since they detect errors with respect to the specific […]