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Posts

Dec, 19

Improving 3D Lattice Boltzmann Method stencil with asynchronous transfers on many-core processors

CPU-based many-core processors present an alternative to multicore CPU and GPU processors. In particular, the 93-Petaflops Sunway supercomputer, built from clustered many-core processors, has opened a new era for high performance computing that does not rely on GPU acceleration. However, memory bandwidth remains the main challenge for these architectures. This motivates our endeavor for optimizing […]
Nov, 30

2D Image Convolution using Three Parallel Programming Models on the Xeon Phi

Image convolution is widely used for sharpening, blurring and edge detection. In this paper, we review two common algorithms for convolving a 2D image by a separable kernel (filter). After optimising the naive codes using loop unrolling and SIMD vectorisation, we choose the algorithm with better performance as the baseline for parallelisation. We then compare […]
Nov, 21

Unified Deep Learning with CPU, GPU, and FPGA Technologies

Deep learning and complex machine learning has quickly become one of the most important computationally intensive applications for a wide variety of fields. The combination of large data sets, high-performance computational capabilities, and evolving and improving algorithms has enabled many successful applications which were previously difficult or impossible to consider. This paper explores the challenges […]
Nov, 16

Domain-Specific Acceleration and Auto-Parallelization of Legacy Scientific Code in FORTRAN 77 using Source-to-Source Compilation

Massively parallel accelerators such as GPGPUs, manycores and FPGAs represent a powerful and affordable tool for scientists who look to speed up simulations of complex systems. However, porting code to such devices requires a detailed understanding of heterogeneous programming tools and effective strategies for parallelization. In this paper we present a source to source compilation […]
Nov, 12

GPU computing and Many Integrated Core Computing (PDP), 2018

TOPICS: * GPU computing, multi GPU processing, hybrid computing * Programming models, programming frameworks, CUDA, OpenCL, communication libraries * Mechanisms for mapping codes * Task allocation * Fault tolerance * Performance analysis * Many Integrated Core architecture, MIC * Intel coprocessor, Xeon Phi * Vectorization * Applications: image processing, signal processing, linear algebra, numerical simulation, […]
Nov, 12

Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms

We present a highly scalable Monte Carlo (MC) 3D photon transport simulation platform designed for heterogeneous computing systems. By developing a massively parallel MC algorithm using the OpenCL framework, this research extends our existing GPU-accelerated MC technique to a highly-scalable vendor-independent heterogeneous computing environment, achieving significantly improved performance and software portability. A number of parallel […]
Nov, 12

Low-power System-on-Chip Processors for Energy Efficient High Performance Computing: The Texas Instruments Keystone II

The High Performance Computing (HPC) community recognizes energy consumption as a major problem. Extensive research is underway to identify means to increase energy efficiency of HPC systems including consideration of alternative building blocks for future systems. This thesis considers one such system, the Texas Instruments Keystone II, a heterogeneous Low-Power System-on-Chip (LPSoC) processor that combines […]
Nov, 7

Radeon PRO Solid State Graphics (SSG) API User Manual

The Radeon Pro SSG software library enables peer-to-peer (P2P) data transfers between GPU and Radeon on board SSD devices. It allows a methodology to read OS file data from SSDs to OpenCL, OpenGL and DirectX buffers with very low-latency P2P communication. The development kit version of this library supports only the Microsoft Windows 10 operating […]
Nov, 5

Data Coherence Analysis and Optimization for Heterogeneous Computing

Although heterogeneous computing has enabled impressive program speed-ups, knowledge about the architecture of the target device is still critical to reap full hardware benefits. Programming such architectures is complex and is usually done by means of specialized languages (e.g. CUDA, OpenCL). The cost of moving and keeping host/device data coherent may easily eliminate any performance […]
Oct, 31

Automatic Scan Parallelization in OpenMP

Prefix Scan (or simply scan) is an operator that computes all the partial sums of a vector. A scan operation results in a vector where each element is the sum of the preceding elements in the original vector up to the corresponding position. Scan is a key operation in many relevant problems like sorting, lexical […]
Oct, 29

A Study of Time and Energy Efficient Algorithms for Parallel and Heterogeneous Computing

This PhD project is motivated by the need to develop and achieve better and energy efficient computing through the use of parallelism and heterogeneous systems. Our contribution consists of both theoretical aspects, as well as in-depth and comprehensive empirical studies that aim to provide more insight into parallel and heterogeneous computing. Our first problem is […]
Oct, 24

A Fast and Generic GPU-Based Parallel Reduction Implementation

Reduction operations are extensively employed in many computational problems. A reduction consists of, given a finite set of numeric elements, combining into a single value all elements in that set, using for this a combiner function. A parallel reduction, in turn, is the reduction operation concurrently performed when multiple execution units are available. The current […]

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