IWOCL

We report on an extension to the C-Reduce tool, for automatic reduction of C test cases, to handle OpenCL kernels. This enables an automated method for detecting bugs in OpenCL compilers, by generating large random kernels using the CLsmith generator, ...

One of the benefits to programming of OpenCL is platform portability. That is, an OpenCL program that follows the OpenCL specification should, in principle, execute reliably on any platform that supports OpenCL. To assess the current state of OpenCL ...

Benchmarking general-purpose computing on graphics processing unit (GPGPU) aims to profile and compare performance across different devices. Due to the low-level nature of most GPGPU APIs, GPGPU benchmarks are also useful for architectural exploration ...

Compiling OpenCL kernels to FPGAs presents a new set of usability challenges. Many OpenCL users are not hardware experts but are creating state-of-the-art hardware with the help of OpenCL compilers for FPGAs. To get great performance the compiler has to ...

In this presentation we focus on current Xilinx FPGA (Field-Programmable Gate Array) platforms with the SDAccel OpenCL environment. FPGA have the unique feature of a reconfigurable architecture by opposition to CPU, GPU or DSP which have a fixed ...

Using computer vision techniques for system-on-chip (SoC) technologies raises performance portability and stringent memory and communication issues for vision applications.

Although high-level libraries like OpenCV abstract both the system-level and ...

Sparse linear algebra is a cornerstone of modern computational science. These algorithms ignore the zero-valued entries found in many domains in order to work on much larger problems at much faster rates than dense algorithms. Nonetheless, optimizing ...

Deep neural networks (DNN) achieved significant breakthrough in vision recognition in 2012 and quickly became the leading machine learning algorithm in Big Data based large scale object recognition applications. The successful deployment of DNN based ...

Modern computing systems are becoming heterogeneous with a variety of programmable units: CPU, GPU, FPGA, domain-specific accelerators, etc. OpenCL™ API is a cross-platform programming model for a wide range of computing devices, but using the language ...

We invite the community to collaboratively design and optimize convolutional neural networks to meet the performance, accuracy and cost requirements for deployment on a range of form factors -- from sensors to self-driving cars.

In this paper we present a novel approach of utilizing new features of OpenCL 2.0: Fine-Grained SVM and device-side enqueue that allow completely new usage models and application paradigms. We present the idea of a GPU (Graphics Processing Unit) daemon ...

In this paper, we explore a number of OpenCL™ optimization strategies and show the pros and cons relative to clFFT, the leading OpenCL Fast Fourier Transform (FFT) library. We implemented a 1D, multi-kernel, mixed-radix Cooley-Tukey power of two ...

OpenCL as an open standard for parallel programming of heterogeneous systems seems to be an attractive choice for software library implementations. Indeed, iwocl.org1 lists 83 OpenCL-enabled libraries as of February 12, 2016, suggesting a healthy ...

Hardware accelerators (HWAs), such as Graphics Processing Units (GPUs) have proven their potential to boost scientific applications performance and have been widely embraced by academia and industry. The OpenCL programming model ensures portability on ...

Boost.Compute is a powerful C++ header-only template library for parallel computing based on OpenCL. It has a layered architecture and acts both as a thin C++ wrapper over the OpenCL API and as a feature-rich interface to high-level constructs that ...

OpenCL™ is an open, royalty-free standard for heterogenous parallel programming. As the number of OpenCL™ platforms is increasing, the requests for better programmability and adoption of modern C++ paradigms is growing bigger. The C++ language is ...

The evolution of many of today's ubiquitous technologies has been possible due to the System on Chip (SoC) technologies. This evolution has triggered an increase of the computing power of hand-held devices, that comes from heterogeneous architectures ...

OpenCL is leveraged to build a flexible, scalable streaming analytics platform using FPGA. The end to end solution can demonstrate over a 2x price/performance advantage over the software baseline. All this can be customized by an application developer ...

The use of GPUs and the massively parallel computing paradigm have become wide-spread. We describe a framework for the interactive visualization and visual analysis of the run-time behavior of massively parallel programs, especially OpenCL kernels. This ...

Autotuning is a popular technique to ensure performance portability for important algorithms such as BLAS, FFT and DNN across the ever evolving software and hardware stack. Unfortunately, when performed on a single machine, autotuning can explore only a ...

n example of a reaction-diffusion equation with chaotic solutions. You can expect patterns to emerge from chaos. A uniformly discretization in space and periodic boundary conditions allows the Fast Fourier Transform to be used, so that when coupled with ...

We present PATOS, a CLANG-based source-to-source compiler to extend the OpenCL kernel language with C++ classes and template types for classes and functions. The generated code is standard conforming OpenCL-C which is usable with unmodified OpenCL ...