high performance computing on graphics processing units: hgpu.org

Agent-Based Simulation (ABS) is a modelling approach where simulated entities i.e., agents, perform actions autonomously and interact with other agents based on a set of rules. ABSs have demonstrated their usefulness in various domains such as transportation, social science, or biology. Agent-based simulators commonly rely vastly on Central Processing Unit (CPU)-based sequential execution. As a […]

Accelerators, such as GPUs (Graphics Processing Unit) that is suitable for handling highly parallel data, and FPGA (Field Programmable Gate Array) with algorithms customized architectures, are widely adopted. The motivation is that algorithms with various parallel characteristics can efficiently map to the heterogeneous computing architecture by collaborated GPU and FPGA. However, current applications always utilize […]

Our goal in this work is to make it easy and feasible to implement solutions for autonomous decision-making and planning under uncertainty on low-power mobile platforms. We focus on practical applications, such as autonomous driving and service robotics, that must run on mobile SoC platforms. These applications often have real-time execution constraints. The main challenge […]

The ever-increasing demand for high-performance Big Data analytics and data processing has paved the way for heterogeneous hardware accelerators, such as Graphics Processing Units (GPUs) and Field Programmable Gate Arrays (FPGAs), to be integrated into modern Big Data platforms. Currently, this integration comes at the cost of programmability, as the end-user Application Programming Interface (API) […]

Field-programmable gate arrays (FPGAs) have garnered significant interest in research on high-performance computing because their flexibility enables the building of application-specific computation pipelines and data supply systems. In addition to the flexibility, toolchains for the development of FPGAs in OpenCL have been developed and offered by FPGA vendors that reduce the programming effort required. However, […]

With the release of the Apple Silicon System-on-a-Chip processors, and the impressive performance shown in general use by both the M1 and M1 Ultra, the potential use for Apple Silicon processors in scientific computing is explored. Both the M1 and M1 Ultra are compared to current state-of-the-art data-center GPUs, including an NVIDIA V100 with PCIe, […]

The continuous technology push on the semiconductor industry has led to the development of several alternate architectures for efficient computing. Field-Programmable Gate Arrays (FPGAs) and Graphics Processing Units (GPUs) are examples of devices used to accelerate applications. FPGAs are able to provide massive parallelism for suitable tasks when properly programmed. However, designing for FPGA is […]

Over the past few years, there has been an increased interest in including FPGAs in data centers and high-performance computing clusters along with GPUs and other accelerators. As a result, it has become increasingly important to have a unified, high-level programming interface for CPUs, GPUs and FPGAs. This has led to the development of compiler […]

We develop BenchPress, the first ML benchmark generator for compilers that is steerable within feature space representations of source code. BenchPress synthesizes compiling functions by adding new code in any part of an empty or existing sequence by jointly observing its left and right context, achieving excellent compilation rate. BenchPress steers benchmark generation towards desired […]

Setting program parameters is challenging due to the abstract relationship between hardware and software. Automatic optimization algorithms that are accurate are required to cope with the complexity and variety of current hardware and software. Autotuning has always relied on time-consuming trial and error approaches. Machine learning (ML) and Natural Language Processing (NLP) has flourished over […]

The ShenWei many-core series processors powering multiple cutting-edge supercomputers are equipped with their unique on-chip heterogeneous architecture. They have long required programmers to write separate codes for the control part on Management Processing Element (MPE) and accelerated part on Compute Processing Element (CPE), which is similar to open standards like OpenCL. Such a programming model […]

With the improvement of global infrastructure, Cyber-Physical Systems (CPS) have become an important component of Industry 4.0. Both the application as well as the machine work together to improve the task of interdependencies. Machine learning methods in CPS require the monitoring of computational algorithms, including adopting optimizations, fine-tuning cyber systems, improving resource utilization, as well […]