high performance computing on graphics processing units: hgpu.org

GPUs gain high popularity in High Performance Computing, due to their massive parallelism and high performance per Watt. Despite their popularity, data transfer between multiple GPUs in a cluster remains a problem. Most communication models require the CPU to control the data flow; also intermediate staging copies to host memory are often inevitable. These two […]

In this paper, we propose a basic technique to minimize the computational time in executing the infinite-stage dynamic programming (DP) on a GPU. The infinite-stage DP involves computations to probe whether a value function gets sufficiently close to the optimal one. Such computations for probing convergence become obvious when an infinite-stage DP is executed on […]

GPU-accelerated data-intensive applications demonstrate in excess of ten-fold speedups over CPU-only approaches. However, file-driven data movement between the CPU and the GPU can degrade performance and energy efficiencies by an order of magnitude as a result of traditional storage latency and ineffectual memory management. In this paper, we first analyze these two critical performance bottlenecks […]

We describe a generic approach to incorporate progressive refinement into GPU-based ray casting. Our approach allows to interactively navigate through highly complex scenes that may usually take several seconds to render while producing high-quality anti-aliased images in late stages of the refinement process. It maintains interactivity by initially evaluating only a small number of screen […]

SAT solving strategies that perform backtracking or clause learning are usually difficult to implement efficiently on massively-parallel architectures because the necessary synchronization does not scale linear with the number of processors available. Strategies like Lookahead Solving and Cube and Conquer are more promising. In order to evaluate a potential GPU implementation of Cube and Conquer, […]

This work describes and demonstrates a novel numerical framework suitable for simulating the behaviour of freely falling liquid droplets. The specific case studied is designed such that the properties of the system are similar to those of raindrops falling through air. The study of raindrops is interesting from both an engineering standpoint and from a […]

The parallel computing power offered by Graphical Processing Units (GPUs) has been recently exploited to support general purpose applications-by exploiting the availability of general API and the SIMT-style parallelism present in several classes of problems (e.g., numerical simulations, matrix manipulations) – where relatively simple computations need to be applied to all items in large sets […]

With processor clock speeds having stagnated, parallel computing architectures have achieved a breakthrough in recent years. Emerging many-core processors like graphics cards run hundreds of threads in parallel and vector instructions are experiencing a revival. Parallel processors with many independent but simple arithmetical logical units fail executing serial tasks efficiently. However, their sheer parallel processing […]

The emergence of compute unified device architecture (CUDA), which has relieved application developers from having to understand complex graphics pipelines, has made the graphics processing unit (GPU) useful not only for graphics applications but also for general applications. In this paper, we present a cycle sharing system named GPU grid, which exploits idle GPU cycles […]

With the decrease in cost of computing, and the increasingly friendly programming environments, the demand for computer generated models of real world problems has surged. Each generation of computer hardware becomes marginally faster than its predecessor, allowing for decreases in required computation time. However, the progression is slowing and will soon reach a barrier as […]

Due to their massive parallelism and high performance per watt GPUs gain high popularity in high performance computing and are a strong candidate for future exacscale systems. But communication and data transfer in GPU accelerated systems remain a challenging problem. Since the GPU normally is not able to control a network device, today a hybrid-programming […]

Memory access efficiency is a key factor for fully exploiting the computational power of Graphics Processing Units (GPUs). However, many details of the GPU memory hierarchy are not released by the vendors. We propose a novel fine-grained benchmarking approach and apply it on two popular GPUs, namely Fermi and Kepler, to expose the previously unknown […]