high performance computing on graphics processing units: hgpu.org

The efficient exploitation of the increasing computational capabilities of mobile devices is still a challenge. The heterogeneity of Systems on Chip (SoC) makes necessary a very specific knowledge of their hardware in order to harness their full potential. OpenCL is a well known standard for cross-platform usage of accelerator devices. We follow an annotation-based approach […]

There is interest in exploring hybrid OpenSHMEM + X programming models to extend the applicability of the OpenSHMEM interface to more hardware architectures. We present a hybrid OpenCL + OpenSHMEM programming model for device-level programming for architectures like the Adapteva Epiphany many-core RISC array processor. The Epiphany architecture comprises a 2D array of low-power RISC […]

Modern mobile devices are equipped with various accelerated processing units to handle computationally intensive applications; therefore, Open Computing Language (OpenCL) has been proposed to fully take advantage of the computational power in heterogeneous systems. This article introduces a parallel software decoder of Low Density Parity Check (LDPC) codes on an embedded heterogeneous platform using an […]

Heterogeneous systems, that marry CPUs and GPUs together in a range of configurations, are quickly becoming the design paradigm for today’s platforms because of their impressive parallel processing capabilities. However, in many existing heterogeneous systems, the GPU is only treated as an accelerator by the CPU, working as a slave to the CPU master. But […]

Computational finance is a domain, where performance is in high demand. Therefore, we investigate the suitability of two families of accelerators for computational finance simulations. Specifically, we use a scenario-based ALM (Asset Liability Management) model and design a suitable OpenCL implementation. We further improve the performance of the application by applying several typical optimization techniques […]

We present a method to classify objects in video streams using a brain-inspired Hierarchical Temporal Memory (HTM) algorithm. Object classification is a challenging task where humans still significantly outperform machine learning algorithms due to their unique capabilities. We have implemented a system which achieves very promising performance in terms of recognition accuracy. Unfortunately, conducting more […]

The release of OpenCL support for FPGAs represents a significant improvement in extending database applications to the reconfigurable domain. Taking advantage of the programmability offered by the OpenCL HLS tool, an OpenCL database can be easily ported and re-designed for FPGAs. A single SQL query in these database systems usually consists of multiple operators, and […]

Today’s computer systems often contains several different processing units aside from the CPU. Among these the GPU is a very common processing unit with an immense compute power that is available in almost all computer systems. How do we make use of this processing power that lies within our machines? One answer is the OpenCL […]

In some digital Earth engineering applications, spatial interpolation algorithms are required to process and analyze large amounts of data. Due to its powerful computing capacity, heterogeneous computing has been used in many applications for data processing in various fields. In this study, we explore the design and implementation of a parallel universal kriging spatial interpolation […]

As the computational trend diverges from standard CPU computing, to encompass GPUs and other accelerators, the need to integrate these unused resources within existing systems becomes apparent. This paper presents the implementation of a HTCondor pool with GPU execution capabilities through OpenCL. Implementation is discussed from both the system setup and the software design standpoint. […]

This paper presents cltorch, a hardware-agnostic backend for the Torch neural network framework. cltorch enables training of deep neural networks on GPUs from diverse hardware vendors, including AMD, NVIDIA, and Intel. cltorch contains sufficient implementation to run models such as AlexNet, VGG, Overfeat, and GoogleNet. It is written using the OpenCL language, a portable compute […]

Erasure coding, Reed-Solomon coding in particular, is a key technique to deal with failures in scale-out storage systems. However, due to the algorithmic complexity, the performance overhead of erasure coding can become a significant bottleneck in storage systems attempting to meet service level agreements (SLAs). Previous work has mainly leveraged SIMD (singleinstruction multiple-data) instruction extensions […]