Skalabilna implementacija dekodera po normi MPEG korištenjem tokovnog programskog jezika

In this paper, we describe a scalable and portable parallelized implementation of a MPEG decoder using a streaming computation paradigm, tailored to new generations of multi--core systems. A novel, hybrid approach towards parallelization of both new and legacy applications is described, where only data--intensive and performance--critical parts are implemented in the streaming domain. An architecture--independent \u27StreamIt\u27 language is used for design, optimization and implementation of parallelized segments, while the developed \u27StreamGate\u27 interface provides a communication mechanism between the implementation domains. The proposed hybrid approach was employed in re--factoring of a reference MPEG video decoder implementation; identifying the most performance--critical segments and re-implementing them in \u27StreamIt\u27 language, with \u27StreamGate\u27 interface as a communication mechanism between the host and streaming kernel. We evaluated the scalability of the decoder with respect to the number of cores, video frame formats, sizes and decomposition. Decoder performance was examined in the presence of different processor load configurations and with respect to the number of simultaneously processed frames.U ovom radu opisujemo skalabilnu i prenosivu implementaciju dekodera po normi MPEG ostvarenu korištenjem paradigme tokovnog računarstva, prilagođenu novim generacijama višejezgrenih računala. Opisan je novi, hibridni pristup paralelizaciji novih ili postojećih aplikacija, gdje se samo podatkovno intenzivni i računski zahtjevni dijelovi implementiraju u tokovnoj domeni. Arhitekturno neovisni jezik StreamIt koristi se za oblikovanje, optimiranje i izvedbu paraleliziranih segmenata aplikacije, dok razvijeno sučelje \u27StreamGate\u27 omogućava komunikaciju između domena implementacije. Predloženi hibridni pristup razvoju paraleliziranih aplikacija iskorišten je u preoblikovanju referentnog dekodera video zapisa po normi MPEG; identificirani su računski zahtjevni segmenti aplikacije i ponovno implementirani u jeziku StreamIt, sa sučeljem \u27StreamGate\u27 kao poveznicom između slijedne i tokovne domene. Ispitivana su svojstva skalabilnosti s obzirom na ciljani broj jezgri, format video zapisa i veličinu okvira te dekompoziciju ulaznih podataka. Svojstva dekodera  su praćena u prisustvu različitih opterećenja ispitnog računala, i s obzirom na broj istovremeno obrađivanih okvira

Doctor of Philosophy

dissertationMemory access irregularities are a major bottleneck for bandwidth limited problems on Graphics Processing Unit (GPU) architectures. GPU memory systems are designed to allow consecutive memory accesses to be coalesced into a single memory access. Noncontiguous accesses within a parallel group of threads working in lock step may cause serialized memory transfers. Irregular algorithms may have data-dependent control flow and memory access, which requires runtime information to be evaluated. Compile time methods for evaluating parallelism, such as static dependence graphs, are not capable of evaluating irregular algorithms. The goals of this dissertation are to study irregularities within the context of unstructured mesh and sparse matrix problems, analyze the impact of vectorization widths on irregularities, and present data-centric methods that improve control flow and memory access irregularity within those contexts. Reordering associative operations has often been exploited for performance gains in parallel algorithms. This dissertation presents a method for associative reordering of stencil computations over unstructured meshes that increases data reuse through caching. This novel parallelization scheme offers considerable speedups over standard methods. Vectorization widths can have significant impact on performance in vectorized computations. Although the hardware vector width is generally fixed, the logical vector width used within a computation can range from one up to the width of the computation. Significant performance differences can occur due to thread scheduling and resource limitations. This dissertation analyzes the impact of vectorization widths on dense numerical computations such as 3D dG postprocessing. It is difficult to efficiently perform dynamic updates on traditional sparse matrix formats. Explicitly controlling memory segmentation allows for in-place dynamic updates in sparse matrices. Dynamically updating the matrix without rebuilding or sorting greatly improves processing time and overall throughput. This dissertation presents a new sparse matrix format, dynamic compressed sparse row (DCSR), which allows for dynamic streaming updates to a sparse matrix. A new method for parallel sparse matrix-matrix multiplication (SpMM) that uses dynamic updates is also presented

Pro++: A Profiling Framework for Primitive-based GPU Programming

Parallelizing software applications through the use of existing optimized primitives is a common trend that mediates the complexity of manual parallelization and the use of less efficient directive-based programming models. Parallel primitive libraries allow software engineers to map any sequential code to a target many-core architecture by identifying the most computational intensive code sections and mapping them into one ore more existing primitives. On the other hand, the spreading of such a primitive-based programming model and the different GPU architectures have led to a large and increasing number of third-party libraries, which often provide different implementations of the same primitive, each one optimized for a specific architecture. From the developer point of view, this moves the actual problem of parallelizing the software application to selecting, among the several implementations, the most efficient primitives for the target platform. This paper presents Pro++, a profiling framework for GPU primitives that allows measuring the implementation quality of a given primitive by considering the target architecture characteristics. The framework collects the information provided by a standard GPU profiler and combines them into optimization criteria. The criteria evaluations are weighed to distinguish the impact of each optimization on the overall quality of the primitive implementation. The paper shows how the tuning of the different weights has been conducted through the analysis of five of the most widespread existing primitive libraries and how the framework has been eventually applied to improve the implementation performance of two standard and widespread primitives

StreamDrive: A Dynamic Dataflow Framework for Clustered Embedded Architectures

In this paper, we present StreamDrive, a dynamic dataflow framework for programming clustered embedded multicore architectures. StreamDrive simplifies development of dynamic dataflow applications starting from sequential reference C code and allows seamless handling of heterogeneous and applicationspecific processing elements by applications. We address issues of ecient implementation of the dynamic dataflow runtime system in the context of constrained embedded environments, which have not been sufficiently addressed by previous research. We conducted a detailed performance evaluation of the StreamDrive implementation on our Application Specic MultiProcessor (ASMP) cluster using the Oriented FAST and Rotated BRIEF (ORB) algorithm typical of image processing domain.We have used the proposed incremental development flow for the transformation of the ORB original reference C code into an optimized dynamic dataflow implementation. Our implementation has less than 10% parallelization overhead, near-linear speedup when the number of processors increases from 1 to 8, and achieves the performance of 15 VGA frames per second with a small cluster configuration of 4 processing elements and 64KB of shared memory, and of 30 VGA frames per second with 8 processors and 128KB of shared memory

Integracija tokovnog modela za učinkovito izvođenje na višejezgrenim računalnim arhitekturama

Streaming has emerged as an important model in present–day applications, ranging from multimedia to scientific computing. Moreover, the emergence of new multicore architectures has resulted with new challenges in efficient utilization of available computational resources. Streaming model offers the portability and scalability of performance with the increasing number of cores. In this paper we propose a tool which enables the implementation of the compute–intensive stream processing kernels as portable modules in general–purpose applications. Resulting modules can be efficiently reused with high degree of scalability in regard to increasing number of processing cores.Tokovni računalni model predstavlja zanimljivo područje istraživanja s ciljem ubrzanja kako multimedijskih, tako i znanstvenih aplikacija. Isto tako, pojava višejezgrenih računalnih arhitektura rezultirala je povećanjem zanimanja za istraživanje metoda i modela koji bi omogućili učinkovito iskorištavanje postojećih paralelnih resursa. Tokovni model omogućuje istovremeno visok stupanj apstrakcije, prenosivost i skalabinost aplikacija s obzirom na povećanje računskih jezgri. U ovom je članku predložen pristup koji omogućuje implementaciju računski zahtjevnih dijelova aplikacija u tokovnom modelu te njihovu integraciju u vidu prenosivih modula. Na taj način ostvareno je ubrzanje cjelokupnih aplikacija pri izvođenju na višejezgrenim procesorima

Parallel, distributed and GPU computing technologies in single-particle electron microscopy

An introduction to the current paradigm shift towards concurrency in software