high performance computing on graphics processing units: hgpu.org

High performance computing (HPC) is now well established as the cornerstone for building and conducting software simulations in numerous scientific and industrial fields. The hardware complexity of supercomputers is steadily increasing, however, to deliver ever improved computing performance, causing the complexity of HPC application development to increase as well. As a result, the need for […]

In the world of algorithm acceleration and the implementation of deep neural networks’ recall phase, OpenCL based solutions have a clear tendency to produce perfectly adapted kernels in graphic processor unit (GPU) architectures. However, they fail to obtain the same results when applied to field-programmable gate array (FPGA) based architectures. This situation, along with an […]

For the last years, we observe the intensive development of accelerated computing platforms. Although current trends indicate a well-established position of GPU devices in the HPC environment, FPGA (Field-Programmable Gate Array) aspires to be an alternative solution to offload the CPU computation. This paper presents a systematic adaptation of four various CFD (Computational Fluids Dynamic) […]

In e-commerce industry, user behavior sequence data has been widely used in many business units such as search and merchandising to improve their products. However, it is rarely used in financial services not only due to its 3V characteristics – i.e. Volume, Velocity and Variety – but also due to its unstructured nature. In this […]

We introduce an automated tool for deploying ultra low-latency, low-power deep neural networks with large convolutional layers on FPGAs. By extending the hls4ml library, we demonstrate how to achieve inference latency of 5μs using convolutional architectures, while preserving state-of-the-art model performance. Considering benchmark models trained on the Street View House Numbers Dataset, we demonstrate various […]

In biology, we are often confronted with information-rich, large-scale trajectory data, but exploring and communicating patterns in such data is often a cumbersome task. Ideally, the data should be wrapped with an interactive visualisation in one concise package that makes it straightforward to create and test hypotheses collaboratively. To address these challenges, we have developed […]

This doctoral thesis covers some of my advances in electron microscopy with deep learning. Highlights include a comprehensive review of deep learning in electron microscopy; large new electron microscopy datasets for machine learning, dataset search engines based on variational autoencoders, and automatic data clustering by t-distributed stochastic neighbour embedding; adaptive learning rate clipping to stabilize […]

Stencil codes (a.k.a. nearest-neighbor computations) are widely used in image processing, machine learning, and scientific applications. Stencil codes incur nearest-neighbor data exchange because the value of each point in the structured grid is calculated as a function of its value and the values of a subset of its nearest-neighbor points. When running on Graphics Processing […]

To apply neural sequence models such as the Transformers to music generation tasks, one has to represent a piece of music by a sequence of tokens drawn from a finite set of pre-defined vocabulary. Such a vocabulary usually involves tokens of various types. For example, to describe a musical note, one needs separate tokens to […]

Scientific computing is at the core of many High-Performance Computing applications, including computational flow dynamics. Because of the uttermost importance to simulate increasingly larger computational models, hardware acceleration is receiving increased attention due to its potential to maximize the performance of scientific computing. A Field-Programmable Gate Array is a reconfigurable hardware accelerator that is fully […]

IWOCL & SYCLcon is the annual gathering of the international community of OpenCL and SYCL developers, researchers, suppliers and Khronos Working Group members to share best practice, and to advance the use and evolution of the Open Computing Language (OpenCL) and the SYCL standard for C++ programming of heterogeneous platforms and their associated ecosystems. This […]

Stencil codes are commonly used to solve many problems. On parallel heterogeneous systems with CPUs and GPUs, the domain is usually split and assigned to GPUs, where it is further divided to GPU blocks. The iterative distributed stencil computation consists of two steps – computation and communication, where the subdomains exchange boundary data, also called […]