high performance computing on graphics processing units: hgpu.org

We describe the multi-GPU gradient boosting algorithm implemented in the XGBoost library. Our algorithm allows fast, scalable training on multi-GPU systems with all of the features of the XGBoost library. We employ data compression techniques to minimise the usage of scarce GPU memory while still allowing highly efficient implementation. Using our algorithm we show that […]

Reconfigurable architectures like Field Programmable Gate Arrays (FPGAs) have been used for accelerating computations from several domains because of their unique combination of flexibility, performance, and power efficiency. However, FPGAs have not been widely used for high-performance computing, primarily because of their programming complexity and difficulties in optimizing performance. In this paper, we present a […]

We study the relationship between memory accesses, bank conflicts, thread multiplicity (also known as over-subscription) and instruction-level parallelism in comparison-based sorting algorithms for Graphics Processing Units (GPUs). We experimentally validate a proposed formula that relates these parameters with asymptotic analysis of the number of memory accesses by an algorithm. Using this formula we analyze and […]

The space of compile-time transformations and or run-time options which can improve the performance of a given code is usually so large as to be virtually impossible to search in any practical time-frame. Thus, heuristics are leveraged which can suggest good but not necessarily best configurations. Unfortunately, since such heuristics are tightly coupled to processor […]

In this thesis, I apply techniques from the field of computer graphics to ray tracing in astrophysical simulations, and introduce the GRACE software library. This is combined with an extant radiative transfer solver to produce a new package, TARANIS. It allows for fully-parallel particle updates via per-particle accumulation of rates, followed by a forward Euler […]

Random program generation – fuzzing – is an effective technique for discovering bugs in compilers but successful fuzzers require extensive development effort for every language supported by the compiler, and often leave parts of the language space untested. We introduce DeepSmith, a novel machine learning approach to accelerating compiler validation through the inference of generative […]

The current interface provided by the C++17 parallel algorithms poses some limitations with respect to parallel data access and heterogeneous systems, such as personal computers and server nodes with GPUs, smartphones, and embedded System on a Chip chipsets. In this paper, we present a summary of why we believe the Ranges TS solves these problems, […]

We present the results of large scale simulations of 4th order nonlinear partial differential equations of dif- fusion type that are typically encountered when modeling dynamics of thin fluid films on substrates. The simulations are based on the alternate direction implicit (ADI) method, with the main part of the compu- tational work carried out in […]

The demand for large compute capabilities in scientific computing led to wide use and acceptance of highly-parallel computer architectures during the last decade. This trend is manifested in the TOP500, listing the fastest supercomputer of the world, in which about 40 % of the performance share results from accelerator-based systems. Programming for these architectures in […]

A heterogeneous architecture composed by a host and an accelerator must frequently deal with situations where several independent tasks are available to be offloaded onto the accelerator. These tasks can be generated by concurrent applications executing in the host or, in case the host is a node of a computer cluster, by applications running on […]

This document outlines the key differences between OpenGL ES and the new Vulkan, and why a developer would want to migrate to Vulkan. Vulkan is a new low level graphics API that allows the developer to get very low level with an almost console-like API. This allows for greater control, performance and transparency. This is […]

The purpose of this paper is to introduce the use of convolutional neural network for prediction of the next appropriate move in the Go game. The paper contains description of the crucial Go game rules, neural networks theory, description of implemented programs and final evaluation of the trained neural networks. The programs were implemented with […]