high performance computing on graphics processing units: hgpu.org

Cardiac dysrhythmia is responsible for over half a million deaths in the United States annually. In this work, we evaluate the performance of neural networks on classifying electrocardiogram (ECG) sequences as normal or abnormal (arrhythmia). Using neural networks as our primary learning model, we explain our model’s performance and discuss hyperparameter tuning. Comparing the results […]

The SEJITS framework supports creating embedded domain-specific languages (DSELs) and code generators, a pair of which is called a specializer, with much less effort than creating a full DSL compiler-typically just a few hundred lines of code. SEJITS’ main benefit is allowing application writers to stay entirely in high-level languages such as Python by using […]

We present a set of algorithms for simulating and visualizing real-time crowds in GPU (Graphics Processing Units) clusters. First we will present crowd simulation and rendering techniques that take advantage of single GPU machines, then using as an example a wandering crowd behavior simulation algorithm, we explain how this kind of algorithms can be extended […]

In recent years, modern graphics processing units have been widely adopted in high performance computing areas to solve large scale computation problems. The leading GPU manufacturers Nvidia and ATI have introduced series of products to the market. While sharing many similar design concepts, GPUs from these two manufacturers differ in several aspects on processor cores […]

Recent technological advances have greatly improved the performance and features of embedded systems. With the number of just mobile devices now reaching nearly equal to the population of earth, embedded systems have truly become ubiquitous. These trends, however, have also made the task of managing their power consumption extremely challenging. In recent years, several techniques […]

Recently, graphics processors (GPUs) have been increasingly leveraged in a variety of scientific computing applications. However, architectural differences between CPUs and GPUs necessitate the development of algorithms that take advantage of GPU hardware. As sparse matrix vector multiplication (SPMV) operations are commonly used in finite element analysis, a new SPMV algorithm and several variations are […]

We present an interpretation of subdivision surface evaluation in the language of linear algebra. Specifically, the vector of surface points can be computed by left-multiplying the vector of control points by a sparse subdivision matrix. This "matrix-driven" interpretation applies to any level of subdivision, holds for many common subdivision schemes (including Catmull-Clark and Loop), supports […]

Accelerator-enhanced computing platforms have drawn a lot of attention due to their massive peak com-putational capacity. Despite significant advances in the pro-gramming interfaces to such hybrid architectures, traditional programming paradigms struggle mapping the resulting multi-dimensional heterogeneity and the expression of algorithm parallelism, resulting in sub-optimal effective performance. Task-based programming paradigms have the capability to alleviate […]

Energy efficiency has been a daunting challenge for datacenters. The financial industry operates some of the largest datacenters in the world. With increasing energy costs and the financial services sector growth, emerging financial analytics workloads may incur extremely high operational costs, to meet their latency targets. Microservers have recently emerged as an alternative to high-end […]

GPUs are widely being used to meet the ever increasing demands of High performance computing. High-end GPUs are one of the highest consumers of power in a computer. Power dissipation has always been a major concern area for computer architects. Due to power efficiency demands modern CPUs have moved towards multicore architectures. GPUs are already […]

We present a parallel framework for simulating incompressible fluids with predictive-corrective incompressible Smoothed Particle Hydrodynamics (PCISPH) on the GPU in real time. To this end, we propose an efficient GPU streaming pipeline to map the entire computational task onto the GPU, fully exploiting the massive computational power of state-of-the-art GPUs. In PCISPH-based simulations, neighbor search […]

When targeting an OpenCL application to platforms with multiple heterogeneous accelerators, task tuning and mapping have to cope with device-specific constraints. To address this problem, we present an innovative design flow for the customization and performance optimization of OpenCL applications on heterogeneous parallel platforms. It consists of two phases: 1) a tuning phase that optimizes […]