high performance computing on graphics processing units: hgpu.org

Mars Rovers are the unmanned machines on planet MARS which are send to analyze and provide details about the planet. GPU and Genetic Algorithms are upcoming technologies used in Mars Rovers for analyzing and sending the data back to the Earth base station. GPU stands for Graphics Processing Unit in which Image compression is the […]

Random Forests are a popular and powerful machine learning technique, with several fast multi-core CPU implementations. Since many other machine learning methods have seen impressive speedups from GPU implementations, applying GPU acceleration to random forests seems like a natural fit. Previous attempts to use GPUs have relied on coarse-grained task parallelism and have yielded inconclusive […]

Due to their potential computation power, GPUs are often used for high performance computing. However, discrete GPUs are connected to the CPU via the PCIe bus, which can cause bottlenecks due to high latency and low bandwidth to the CPU. Lately, integrated GPUs have become more common, and due to being integrated on the CPU-chip, […]

Volume rendering has always been a popular topic in computer graphics as it captures more realistic rendering results. However, most of the rendering targets are focused on participating media distributed in the scene. In this project we integrate an Octree data structure with our path tracer in CUDA to achieve efficient volume rendering of models. […]

We propose a method for preconditioner construction and parallel implementations of the Preconditioned Conjugate Gradient algorithm on GPU platforms. The preconditioning matrix is an approximate inverse derived from an algorithm for the iterative improvement of a solution to linear equations. Using a sparse matrix-vector product, our preconditioner is well suited for massively parallel GPU architecture. […]

We present direct astrophysical N-body simulations with up to a few million bodies using our parallel MPI/CUDA code on large GPU clusters in China, Ukraine and Germany, with different kinds of GPU hardware. These clusters are directly linked under the Chinese Academy of Sciences special GPU cluster program in the cooperation of ICCS (International Center […]

We develop a systematic Bayesian framework for physics constrained parameter inference of stochastic differential equations (SDE) from partial observations. The physical constraints are derived for stochastic climate models but are applicable for many fluid systems. We first derive a condition for the Lyapunov stability of stochastic climate models based on energy conservation. Stochastic climate models […]

Graphics processing units (GPUs) in a computer system are increasingly adopted to create a realistic environment in 3D applications. Despite the extremely high parallelism of these devices with a tremendous amount of processing elements, GPUs are seldom used in scientific applications owing to their difficulty in programming. Additionally, vendor-provided APIs are too specific to cross […]

Although the performance of image acquisition devices has been improved dramatically in recent years, especially in the resolution and clarity, defocusing and motion blur are still big problems. Upgrading the devices with the better hardware is one way to solve the problem, but the costs will usually increase disproportionately comparing with what we get. The […]

We propose an adaptability judging method applied to sparse matrices and the target cache memory using two metrics based on spatial locality and temporal locality. For indirect access sequences of sparse matrix-vector multiplications, one metric is the number of valid data within a cache line, and another metric is average reference interval. We also develop […]

We propose a real-time approach to learning semantic maps from moving RGB-D cameras. Our method models geometry, appearance, and semantic labeling of surfaces. We recover camera pose using simultaneous localization and mapping while concurrently recognizing and segmenting object classes in the images. Our object-class segmentation approach is based on random decision forests and yields a […]

Ultrasound scanners are often used in medical diagnostics for visualising body parts without entering the body. An image is created by visualising reflections from an ultrasound pulse, transmitted into the body. Current scanners use a scanning which creates an image line by line, using focused pulses on each line separately. This method results in high […]