high performance computing on graphics processing units: hgpu.org

I present RoadRunner, a fast exoplanet transit model that can use any radially symmetric function to model stellar limb darkening while still being faster to evaluate than the analytical transit model for quadratic limb darkening by Mandel & Agol (2002). CPU and GPU implementations of the model are available in the PyTransit transit modelling package, […]

In the past decade, high performance compute capabilities exhibited by heterogeneous GPGPU platforms have led to the popularity of data parallel programming languages such as CUDA and OpenCL. Such languages, however, involve a steep learning curve as well as developing an extensive understanding of the underlying architecture of the compute devices in heterogeneous platforms. This […]

First, we present techniques to efficiently schedule data transfers through compiler analyses. Compared to transferring data immediately before and after the kernel executes, our scheduling results in orders of magnitude improvements in execution time, number of data transfers, and number of bytes transferred. Second, we demonstrate techniques to provide on-chip debugging for heterogeneous systems through […]

This thesis shows that it is feasible to build modular FPGA systems which can dynamically change the hardware resources in the spatial and the temporal domains using existing tools and accelerators, to improve maintainability, adaptability, and accessibility for FPGA systems. To achieve this, first, a modular FPGA development flow is proposed to build an FPGA […]

Compyle allows users to execute a restricted subset of Python on a variety of HPC platforms. It is an embedded domain-specific language (eDSL) for parallel computing. It currently supports multi-core execution using Cython, and OpenCL and CUDA for GPU devices. Users write code in a restricted subset of Python that is automatically transpiled to high-performance […]

The Graphics Processing Unit (GPU) is a co-processor designed to aid the Central Processing Unit (CPU) for rendering 3D graphics. The prompt development of these graphics chips due to the popularity of games and media design helped the GPU to evolve its ubiquitous parallel architecture. The programmability of these devices increased with the introduction of […]

==================================================== The Fifth International Workshop on GPU Computing and AI (GCA’20) to be held in conjunction with The Eighth International Symposium on Computing and Networking (CANDAR’20),Naha, Okinawa, Japan, November 24-27, 2020 ==================================================== Special announcement regarding COVID-19 situation– Although we are still working with the possibility of having physical meetings for CANDAR 2020 as planned, the […]

The Boolean satisfiability problem, abbreviated as SAT, is the backbone of many applications in VLSI design automation and verification. Over the years, many SAT solvers, both complete and incomplete, have been developed. Complete solvers are usually based on the DPLL (Davis–Putnam–Logemann–Loveland) algorithm, which is a backtracking algorithm. Industrial strength problems are very large and make […]

We apply the SYCL programming model to the Rodinia benchmark suite, describe the transformations from the OpenCL implementations to the SYCL implementations, and evaluate the benchmarks on microprocessors with a CPU and an integrated GPU. The publicly available implementations of the benchmark suite will track the development of the SYCL compilers, and provide programs for […]

The execution of agent-based simulations (ABSs) on hardware accelerator devices such as graphics processing units (GPUs) has been shown to offer great performance potentials. However, in heterogeneous hardware environments, it can become increasingly difficult to find viable partitions of the simulation and provide implementations for different hardware devices. To automate this process, we present OpenABLext, […]

The fundamental operation of matrix multiplication is ubiquitous across a myriad of disciplines. Yet, the identification of new optimizations for matrix multiplication remains relevant for emerging hardware architectures and heterogeneous systems. Frameworks such as OpenCL enable computation orchestration on existing systems, and its availability using the Intel High Level Synthesis compiler allows users to architect […]

SYCL is a parallel programming model for developing single-source programs for running on heterogeneous platforms. To this end, it allows for one code to be written which can run on a different architectures. For this study, we develop applications in SYCL which are representative of those often used in High-Performance Computing. Their performance is benchmarked […]