Multi-GPU maximum entropy image synthesis for radio astronomy

The maximum entropy method (MEM) is a well known deconvolution technique in radio-interferometry. This method solves a non-linear optimization problem with an entropy regularization term. Other heuristics such as CLEAN are faster but highly user dependent. Nevertheless, MEM has the following advantages: it is unsupervised, it has a statistical basis, it has a better resolution and better image quality under certain conditions. This work presents a high performance GPU version of non-gridding MEM, which is tested using real and simulated data. We propose a single-GPU and a multi-GPU implementation for single and multi-spectral data, respectively. We also make use of the Peer-to-Peer and Unified Virtual Addressing features of newer GPUs which allows to exploit transparently and efficiently multiple GPUs. Several ALMA data sets are used to demonstrate the effectiveness in imaging and to evaluate GPU performance. The results show that a speedup from 1000 to 5000 times faster than a sequential version can be achieved, depending on data and image size. This allows to reconstruct the HD142527 CO(6-5) short baseline data set in 2.1 minutes, instead of 2.5 days that takes a sequential version on CPU.Comment: 11 pages, 13 figure

A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications

Particle swarm optimization (PSO) is a heuristic global optimization method, proposed originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used optimization techniques. This survey presented a comprehensive investigation of PSO. On one hand, we provided advances with PSO, including its modifications (including quantum-behaved PSO, bare-bones PSO, chaotic PSO, and fuzzy PSO), population topology (as fully connected, von Neumann, ring, star, random, etc.), hybridization (with genetic algorithm, simulated annealing, Tabu search, artificial immune system, ant colony algorithm, artificial bee colony, differential evolution, harmonic search, and biogeography-based optimization), extensions (to multiobjective, constrained, discrete, and binary optimization), theoretical analysis (parameter selection and tuning, and convergence analysis), and parallel implementation (in multicore, multiprocessor, GPU, and cloud computing forms). On the other hand, we offered a survey on applications of PSO to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research, mechanical engineering, fuel and energy, medicine, chemistry, and biology. It is hoped that this survey would be beneficial for the researchers studying PSO algorithms

Multiprocessor System-on-Chips based Wireless Sensor Network Energy Optimization

Wireless Sensor Network (WSN) is an integrated part of the Internet-of-Things (IoT) used to monitor the physical or environmental conditions without human intervention. In WSN one of the major challenges is energy consumption reduction both at the sensor nodes and network levels. High energy consumption not only causes an increased carbon footprint but also limits the lifetime (LT) of the network. Network-on-Chip (NoC) based Multiprocessor System-on-Chips (MPSoCs) are becoming the de-facto computing platform for computationally extensive real-time applications in IoT due to their high performance and exceptional quality-of-service. In this thesis a task scheduling problem is investigated using MPSoCs architecture for tasks with precedence and deadline constraints in order to minimize the processing energy consumption while guaranteeing the timing constraints. Moreover, energy-aware nodes clustering is also performed to reduce the transmission energy consumption of the sensor nodes. Three distinct problems for energy optimization are investigated given as follows: First, a contention-aware energy-efficient static scheduling using NoC based heterogeneous MPSoC is performed for real-time tasks with an individual deadline and precedence constraints. An offline meta-heuristic based contention-aware energy-efficient task scheduling is developed that performs task ordering, mapping, and voltage assignment in an integrated manner. Compared to state-of-the-art scheduling our proposed algorithm significantly improves the energy-efficiency. Second, an energy-aware scheduling is investigated for a set of tasks with precedence constraints deploying Voltage Frequency Island (VFI) based heterogeneous NoC-MPSoCs. A novel population based algorithm called ARSH-FATI is developed that can dynamically switch between explorative and exploitative search modes at run-time. ARSH-FATI performance is superior to the existing task schedulers developed for homogeneous VFI-NoC-MPSoCs. Third, the transmission energy consumption of the sensor nodes in WSN is reduced by developing ARSH-FATI based Cluster Head Selection (ARSH-FATI-CHS) algorithm integrated with a heuristic called Novel Ranked Based Clustering (NRC). In cluster formation parameters such as residual energy, distance parameters, and workload on CHs are considered to improve LT of the network. The results prove that ARSH-FATI-CHS outperforms other state-of-the-art clustering algorithms in terms of LT.University of Derby, Derby, U

Running stream-like programs on heterogeneous multi-core systems

All major semiconductor companies are now shipping multi-cores. Phones, PCs, laptops, and mobile internet devices will all require software that can make effective use of these cores. Writing high-performance parallel software is difficult, time-consuming and error prone, increasing both time-to-market and cost. Software outlives hardware; it typically takes longer to develop new software than hardware, and legacy software tends to survive for a long time, during which the number of cores per system will increase. Development and maintenance productivity will be improved if parallelism and technical details are managed by the machine, while the programmer reasons about the application as a whole. Parallel software should be written using domain-specific high-level languages or extensions. These languages reveal implicit parallelism, which would be obscured by a sequential language such as C. When memory allocation and program control are managed by the compiler, the program's structure and data layout can be safely and reliably modified by high-level compiler transformations. One important application domain contains so-called stream programs, which are structured as independent kernels interacting only through one-way channels, called streams. Stream programming is not applicable to all programs, but it arises naturally in audio and video encode and decode, 3D graphics, and digital signal processing. This representation enables high-level transformations, including kernel unrolling and kernel fusion. This thesis develops new compiler and run-time techniques for stream programming. The first part of the thesis is concerned with a statically scheduled stream compiler. It introduces a new static partitioning algorithm, which determines which kernels should be fused, in order to balance the loads on the processors and interconnects. A good partitioning algorithm is crucial if the compiler is to produce efficient code. The algorithm also takes account of downstream compiler passes---specifically software pipelining and buffer allocation---and it models the compiler's ability to fuse kernels. The latter is important because the compiler may not be able to fuse arbitrary collections of kernels. This thesis also introduces a static queue sizing algorithm. This algorithm is important when memory is distributed, especially when local stores are small. The algorithm takes account of latencies and variations in computation time, and is constrained by the sizes of the local memories. The second part of this thesis is concerned with dynamic scheduling of stream programs. First, it investigates the performance of known online, non-preemptive, non-clairvoyant dynamic schedulers. Second, it proposes two dynamic schedulers for stream programs. The first is specifically for one-dimensional stream programs. The second is more general: it does not need to be told the stream graph, but it has slightly larger overhead. This thesis also introduces some support tools related to stream programming. StarssCheck is a debugging tool, based on Valgrind, for the StarSs task-parallel programming language. It generates a warning whenever the program's behaviour contradicts a pragma annotation. Such behaviour could otherwise lead to exceptions or race conditions. StreamIt to OmpSs is a tool to convert a streaming program in the StreamIt language into a dynamically scheduled task based program using StarSs.Totes les empreses de semiconductors produeixen actualment multi-cores. Mòbils,PCs, portàtils, i dispositius mòbils d’Internet necessitaran programari quefaci servir eficientment aquests cores. Escriure programari paral·lel d’altrendiment és difícil, laboriós i propens a errors, incrementant tant el tempsde llançament al mercat com el cost. El programari té una vida més llarga queel maquinari; típicament pren més temps desenvolupar nou programi que noumaquinari, i el programari ja existent pot perdurar molt temps, durant el qualel nombre de cores dels sistemes incrementarà. La productivitat dedesenvolupament i manteniment millorarà si el paral·lelisme i els detallstècnics són gestionats per la màquina, mentre el programador raona sobre elconjunt de l’aplicació.El programari paral·lel hauria de ser escrit en llenguatges específics deldomini. Aquests llenguatges extrauen paral·lelisme implícit, el qual és ocultatper un llenguatge seqüencial com C. Quan l’assignació de memòria i lesestructures de control són gestionades pel compilador, l’estructura iorganització de dades del programi poden ser modificades de manera segura ifiable per les transformacions d’alt nivell del compilador.Un dels dominis de l’aplicació importants és el que consta dels programes destream; aquest programes són estructurats com a nuclis independents queinteractuen només a través de canals d’un sol sentit, anomenats streams. Laprogramació de streams no és aplicable a tots els programes, però sorgeix deforma natural en la codificació i descodificació d’àudio i vídeo, gràfics 3D, iprocessament de senyals digitals. Aquesta representació permet transformacionsd’alt nivell, fins i tot descomposició i fusió de nucli.Aquesta tesi desenvolupa noves tècniques de compilació i sistemes en tempsd’execució per a programació de streams. La primera part d’aquesta tesi esfocalitza amb un compilador de streams de planificació estàtica. Presenta unnou algorisme de partició estàtica, que determina quins nuclis han de serfusionats, per tal d’equilibrar la càrrega en els processadors i en lesinterconnexions. Un bon algorisme de particionat és fonamental per tal de queel compilador produeixi codi eficient. L’algorisme també té en compte elspassos de compilació subseqüents---específicament software pipelining il’arranjament de buffers---i modela la capacitat del compilador per fusionarnuclis. Aquesta tesi també presenta un algorisme estàtic de redimensionament de cues.Aquest algorisme és important quan la memòria és distribuïda, especialment quanles memòries locals són petites. L’algorisme té en compte latències ivariacions en els temps de càlcul, i considera el límit imposat per la mida deles memòries locals.La segona part d’aquesta tesi es centralitza en la planificació dinàmica deprogrames de streams. En primer lloc, investiga el rendiment dels planificadorsdinàmics online, non-preemptive i non-clairvoyant. En segon lloc, proposa dosplanificadors dinàmics per programes de stream. El primer és específicament pera programes de streams unidimensionals. El segon és més general: no necessitael graf de streams, però els overheads són una mica més grans.Aquesta tesi també presenta un conjunt d’eines de suport relacionades amb laprogramació de streams. StarssCheck és una eina de depuració, que és basa enValgrind, per StarSs, un llenguatge de programació paral·lela basat en tasques.Aquesta eina genera un avís cada vegada que el comportament del programa estàen contradicció amb una anotació pragma. Aquest comportament d’una altra manerapodria causar excepcions o situacions de competició. StreamIt to OmpSs és unaeina per convertir un programa de streams codificat en el llenguatge StreamIt aun programa de tasques en StarSs planificat de forma dinàmica.Postprint (published version

Parallelism and the software-hardware interface in embedded systems

This thesis by publications addresses issues in the architecture and microarchitecture of next generation, high performance streaming Systems-on-Chip through quantifying the most important forms of parallelism in current and emerging embedded system workloads. The work consists of three major research tracks, relating to data level parallelism, thread level parallelism and the software-hardware interface which together reflect the research interests of the author as they have been formed in the last nine years. Published works confirm that parallelism at the data level is widely accepted as the most important performance leverage for the efficient execution of embedded media and telecom applications and has been exploited via a number of approaches the most efficient being vectorlSIMD architectures. A further, complementary and substantial form of parallelism exists at the thread level but this has not been researched to the same extent in the context of embedded workloads. For the efficient execution of such applications, exploitation of both forms of parallelism is of paramount importance. This calls for a new architectural approach in the software-hardware interface as its rigidity, manifested in all desktop-based and the majority of embedded CPU's, directly affects the performance ofvectorized, threaded codes. The author advocates a holistic, mature approach where parallelism is extracted via automatic means while at the same time, the traditionally rigid hardware-software interface is optimized to match the temporal and spatial behaviour of the embedded workload. This ultimate goal calls for the precise study of these forms of parallelism for a number of applications executing on theoretical models such as instruction set simulators and parallel RAM machines as well as the development of highly parametric microarchitectural frameworks to encapSUlate that functionality.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Hardware/Software Co-design for Multicore Architectures

Siirretty Doriast

The 1992 4th NASA SERC Symposium on VLSI Design

Papers from the fourth annual NASA Symposium on VLSI Design, co-sponsored by the IEEE, are presented. Each year this symposium is organized by the NASA Space Engineering Research Center (SERC) at the University of Idaho and is held in conjunction with a quarterly meeting of the NASA Data System Technology Working Group (DSTWG). One task of the DSTWG is to develop new electronic technologies that will meet next generation electronic data system needs. The symposium provides insights into developments in VLSI and digital systems which can be used to increase data systems performance. The NASA SERC is proud to offer, at its fourth symposium on VLSI design, presentations by an outstanding set of individuals from national laboratories, the electronics industry, and universities. These speakers share insights into next generation advances that will serve as a basis for future VLSI design

Efficient Techniques for Wave-based Sound Propagation in Interactive Applications

Sound propagation techniques model the effect of the environment on sound waves and predict their behavior from point of emission at the source to the final point of arrival at the listener. Sound is a pressure wave produced by mechanical vibration of a surface that propagates through a medium such as air or water, and the problem of sound propagation can be formulated mathematically as a second-order partial differential equation called the wave equation. Accurate techniques based on solving the wave equation, also called the wave-based techniques, are too expensive computationally and memory-wise. Therefore, these techniques face many challenges in terms of their applicability in interactive applications including sound propagation in large environments, time-varying source and listener directivity, and high simulation cost for mid-frequencies. In this dissertation, we propose a set of efficient wave-based sound propagation techniques that solve these three challenges and enable the use of wave-based sound propagation in interactive applications. Firstly, we propose a novel equivalent source technique for interactive wave-based sound propagation in large scenes spanning hundreds of meters. It is based on the equivalent source theory used for solving radiation and scattering problems in acoustics and electromagnetics. Instead of using a volumetric or surface-based approach, this technique takes an object-centric approach to sound propagation. The proposed equivalent source technique generates realistic acoustic effects and takes orders of magnitude less runtime memory compared to prior wave-based techniques. Secondly, we present an efficient framework for handling time-varying source and listener directivity for interactive wave-based sound propagation. The source directivity is represented as a linear combination of elementary spherical harmonic sources. This spherical harmonic-based representation of source directivity can support analytical, data-driven, rotating or time-varying directivity function at runtime. Unlike previous approaches, the listener directivity approach can be used to compute spatial audio (3D audio) for a moving, rotating listener at interactive rates. Lastly, we propose an efficient GPU-based time-domain solver for the wave equation that enables wave simulation up to the mid-frequency range in tens of minutes on a desktop computer. It is demonstrated that by carefully mapping all the components of the wave simulator to match the parallel processing capabilities of the graphics processors, significant improvement in performance can be achieved compared to the CPU-based simulators, while maintaining numerical accuracy. We validate these techniques with offline numerical simulations and measured data recorded in an outdoor scene. We present results of preliminary user evaluations conducted to study the impact of these techniques on user's immersion in virtual environment. We have integrated these techniques with the Half-Life 2 game engine, Oculus Rift head-mounted display, and Xbox game controller to enable users to experience high-quality acoustics effects and spatial audio in the virtual environment.Doctor of Philosoph