high performance computing on graphics processing units: hgpu.org

Dense linear algebra (DLA) has historically been in the vanguard of software that must be adapted first to hardware changes. This is because DLA is both critical to the accuracy and performance of so many different types of applications, and because they have proved to be outstanding vehicles for finding and implementing solutions to the […]

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 […]

The plethora of complex artificial intelligence (AI) algorithms and available high performance computing (HPC) power stimulates the convergence of AI and HPC. The expeditious development of AI components, in both hardware and software domain, increases the system heterogeneity, which prompts the challenge on fair and comprehensive benchmarking. Existing HPC and AI benchmarks fail to cover […]

GPU accelerators have become an important backbone for scientific high performance computing, and the performance advances obtained from adopting new GPU hardware are significant. In this paper we take a first look at NVIDIA’s newest server line GPU, the A100 architecture part of the Ampere generation. Specifically, we assess its performance for sparse linear algebra […]

This doctoral thesis focuses on GPU acceleration of medical image registration and sparse general matrix-matrix multiplication (SpGEMM). The comprehensive work presented here aims to enable new possibilities in Image Guided Surgery (IGS). IGS provides the surgeon with advanced navigation tools during surgery. Image registration, which is a part of IGS, is computationally demanding, therefore GPU […]

During recent years, big data explosion and the increase in main memory capacity, on the one hand, and the need for faster data processing, on the other hand, have caused the development of various in-memory processing tools to manage and analyze data. Engaging the speed of the main memory and advantaging data locality, these tools […]

Data management systems commonly use bitmap indices to increase the efficiency of querying scientific data. Bitmaps are usually highly compressible and can be queried directly using fast hardware-supported bitwise logical operations. The processing of bitmap queries is inherently parallel in structure, which suggests they could benefit from concurrent computer systems. In particular, bitmap-range queries offer […]

Pose estimation of known objects is fundamental to tasks such as robotic grasping and manipulation. The need for reliable grasping imposes stringent accuracy requirements on pose estimation in cluttered, occluded scenes in dynamic environments. Modern methods employ large sets of training data to learn features in order to find correspondence between 3D models and observed […]

FPGAs excel in low power and high throughput computations, but they are challenging to program. Traditionally, developers rely on hardware description languages like Verilog or VHDL to specify the hardware behavior at the register-transfer level. High-Level Synthesis (HLS) raises the level of abstraction, but still requires FPGA design knowledge. Programmers usually write pragma-annotated C/C++ programs […]

We present a simple compilation strategy for safety-checking array indexing in high-level languages on GPUs. Our technique does not depend on hardware support for abnormal termination, and is designed to be efficient in the non-failing case. We rely on certain properties of array languages, namely the absence of arbitrary cross-thread communication, to ensure well-defined execution […]

OpenSBLI is an open-source code-generation system for compressible fluid dynamics (CFD) on heterogeneous computing architectures. Written in Python, OpenSBLI is an explicit high-order finite-difference solver on structured curvilinear meshes. Shock-capturing is performed by a choice of high-order Weighted Essentially Non-Oscillatory (WENO) or Targeted Essentially Non-Oscillatory (TENO) schemes. OpenSBLI generates a complete CFD solver in the […]