Heterogeneous architectures, by definition, include multiple processing components with very different microarchitectures and execution models. In particular, computing platforms from supercomputers to smartphones can now incorporate both CPU and GPU processors. Disparities between CPU and GPU processor architectures have naturally led to distinct programming models and development patterns for...

Received Day Month Year Revised Day Month Year This work presents a methodology for studying active Brownian dynamics on ratchet potentials using interoperating OpenCL and OpenGL frameworks. Programing details along with optimization issues are discussed, followed by a comparison of performance on different devices. Time of visualization using OpenGL sharing buffer with OpenCL has been tested a...

OpenCL is a relatively new standard that supports computation on a variety of parallel architectures. The author was unable to find reliable information about performance of OpenCL programs on CPU’s in comparison to traditional parallel processing standards like OpenMP. This paper describes the results of an experiment that tries to answer the following question: “Which standard performs better...

With the success of programming models such as Khronos’ OpenCL, heterogeneous computing is going mainstream. However, these models are low-level, even when considering them as systems programming models. For example, OpenCL is effectively an extended subset of C99, limited to the type unsafe procedural abstraction that C has provided for more than 30 years. Computer systems programming has for ...

OpenCL is an open standard for parallel programming of heterogeneous compute devices, such as GPUs, CPUs, DSPs or FPGAs. However, the verbosity of its C host API can hinder application development. In this paper we present cf4ocl, a software library for rapid development of OpenCL programs in pure C. It aims to reduce the verbosity of the OpenCL API, offering straightforward memory management, ...

Multicore/manycore architecture accelerates demand for a new programming environment to utilize the massive processors integrated in an LSI. GPU (Graphics Processing Unit) is one of the typical hardware environments. The programming environments on GPU are traditionally vendor-/hardware-specific, where complicate the management of uniform programs that access computing resources of the massivel...

We present an effective technique for crosschecking a C or C++ program against an accelerated OpenCL version, as well as a technique for detecting data races in OpenCL programs. Our techniques are implemented in KLEE-CL, a symbolic execution engine based on KLEE and KLEE-FP that supports symbolic reasoning on the equivalence between symbolic values. Our approach is to symbolically model the Ope...

Current processor architectures are diverse and heterogeneous. Examples include multicore chips, GPUs and the Cell Broadband Engine (CBE). The recent Open Compute Language (OpenCL) standard aims at efficiency and portability. This paper explores its efficiency when implemented on the CBE, without using CBE-specific features such as explicit asynchronous memory transfers. We based our experiment...

In this work, we evaluate OpenCL as a programming tool for developing performanceportable applications for GPGPU. While the Khronos group developed OpenCL with programming portability in mind, performance is not necessarily portable. OpenCL has required performance-impacting initializations that do not exist in other languages such as CUDA. Understanding these implications allows us to provide ...

In recent years, with the increasing computing power and programmability on GPU, GPU has become an important role on hardware accelerator. Heterogeneous System Architecture (HSA) announced by HSA Foundation is an approach to benefit both CPUs and GPUs advantages. Open Computing Language (OpenCL) is one of the wellknown programming frameworks for parallel computing on heterogeneous architecture....