Performance of HEVC Discrete Cosine and Sine Transforms GPU
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CALIFORNIA STATE UNIVERSITY, NORTHRIDGE Optimized AV1 Inter
CALIFORNIA STATE UNIVERSITY, NORTHRIDGE Optimized AV1 Inter Prediction using Binary classification techniques A graduate project submitted in partial fulfillment of the requirements for the degree of Master of Science in Software Engineering by Alex Kit Romero May 2020 The graduate project of Alex Kit Romero is approved: ____________________________________ ____________ Dr. Katya Mkrtchyan Date ____________________________________ ____________ Dr. Kyle Dewey Date ____________________________________ ____________ Dr. John J. Noga, Chair Date California State University, Northridge ii Dedication This project is dedicated to all of the Computer Science professors that I have come in contact with other the years who have inspired and encouraged me to pursue a career in computer science. The words and wisdom of these professors are what pushed me to try harder and accomplish more than I ever thought possible. I would like to give a big thanks to the open source community and my fellow cohort of computer science co-workers for always being there with answers to my numerous questions and inquiries. Without their guidance and expertise, I could not have been successful. Lastly, I would like to thank my friends and family who have supported and uplifted me throughout the years. Thank you for believing in me and always telling me to never give up. iii Table of Contents Signature Page ................................................................................................................................ ii Dedication ..................................................................................................................................... -
Video Compression Optimized for Racing Drones
Video compression optimized for racing drones Henrik Theolin Computer Science and Engineering, master's level 2018 Luleå University of Technology Department of Computer Science, Electrical and Space Engineering Video compression optimized for racing drones November 10, 2018 Preface To my wife and son always! Without you I'd never try to become smarter. Thanks to my supervisor Staffan Johansson at Neava for providing room, tools and the guidance needed to perform this thesis. To my examiner Rickard Nilsson for helping me focus on the task and reminding me of the time-limit to complete the report. i of ii Video compression optimized for racing drones November 10, 2018 Abstract This thesis is a report on the findings of different video coding tech- niques and their suitability for a low powered lightweight system mounted on a racing drone. Low latency, high consistency and a robust video stream is of the utmost importance. The literature consists of multiple comparisons and reports on the efficiency for the most commonly used video compression algorithms. These reports and findings are mainly not used on a low latency system but are testing in a laboratory environment with settings unusable for a real-time system. The literature that deals with low latency video streaming and network instability shows that only a limited set of each compression algorithms are available to ensure low complexity and no added delay to the coding process. The findings re- sulted in that AVC/H.264 was the most suited compression algorithm and more precise the x264 implementation was the most optimized to be able to perform well on the low powered system. -
Wen-Mei William Hwu
Wen-mei William Hwu PERSONAL INFORMATION Office: Home: Coordinated Science Laboratory 2709 Bayhill Drive 1308 West Main Street, Champaign, Illinois, 61822-7988 Urbana, Illinois, 61801-2307 (217) 359-8984 (217) 244-8270 (217) 333-5579 (FAX) Email: [email protected] EDUCATION Ph.D., Computer Science,1987, University of California, Berkeley B.S., Electrical Engineering, 1983, National Taiwan University, Taiwan CURRENT POSITION Professor and Sanders III Advanced Micro Devices, Inc., Endowed Chair, Electrical and Computer Engineering; Research Professor of Coordinated Science Laboratory, University of Illinois, Urbana-Champaign (UIUC). Chief Technology Officer and Co-Founder, MulticoreWare, Sunnnyvale, California, St. Louis, Missouri, Champaign, Illinois, Chennai, India, Chang-Chun and Beijing, China. Chief Scientist, Parallel Computing Institute, University of Illinois at Urbana-Champaign Board Member, Personify, Inc., Champaign, IL PROFESSIONAL EXPERIENCE September 2016 to present Co-Director (with Jinjun Xiong of IBM) of the IBM-Illinois Center for Cognitive Computing Systems Research, funded by IBM at a total of $8M for five years. The center funds a total of 30+ researchers working on hardware, software, and algorithms for building cognitive computing systems for innovative AI applications. June 2010 to present Co-Director (with Mateo Valero) of the PUMPS Summer School in Barcelona jointly offered by UIUC and the Universitat Politècnica de Catalunya. The summer school has been attended by about 100 faculty and graduate students worldwide every year to study the advanced parallel algorithm techniques for manycore computing systems. June 2008 to present Principle Investigator of the UIUC CUDA Center of Excellence, funded by NVIDIA at over $2.0 M in cash and equipment. -
Opencl BOF Aug14
Neil Trevett Vice President Mobile Ecosystem at NVIDIA President of Khronos and Chair of the OpenCL Working Group SIGGRAPH, Vancouver 2014 © Copyright Khronos Group 2014 - Page 1 Speakers Neil Trevett OpenCL Chair, VP NVIDIA NVIDIA Introduction to Khronos and OpenCL Ecosystem Ralph Potter Research Engineer Codeplay SPIR Luke Iwanski Games Technology Programmer Codeplay SYCL Laszlo Kishonti CEO Kishonti Compute Benchmarking Neil Trevett OpenCL Chair, VP NVIDIA NVIDIA Wrap-up and Questions © Copyright Khronos Group 2014 - Page 2 OpenCL – Portable Heterogeneous Computing • Portable Heterogeneous programming of diverse compute resources - Targeting supercomputers -> embedded systems -> mobile devices • One code tree can be executed on CPUs, GPUs, DSPs and hardware - Dynamically interrogate system load and balance work across available processors • OpenCL = Two APIs and C-based Kernel language - Platform Layer API to query, select and initialize compute devices - Kernel language - Subset of ISO C99 + language extensions - C Runtime API to build and execute kernels across multiple devices OpenCL KernelOpenCL CodeKernel OpenCL CodeKernel OpenCL CodeKernel Code GPU DSP CPU CPU HW © Copyright Khronos Group 2014 - Page 3 OpenCL Roadmap • What markets has OpenCL been aimed at? • What problems is OpenCL solving? • How will OpenCL need to adapt in the future? HPC HPC HPC Desktop HPC Discussion Desktop Desktop Mobile Focus for New Desktop Mobile Mobile Web Capabilities Mobile Web Web FPGA FPGA Embedded Safety Critical 3-component vectors Shared Virtual -
Answers to Exercises
Answers to Exercises A bird does not sing because he has an answer, he sings because he has a song. —Chinese Proverb Intro.1: abstemious, abstentious, adventitious, annelidous, arsenious, arterious, face- tious, sacrilegious. Intro.2: When a software house has a popular product they tend to come up with new versions. A user can update an old version to a new one, and the update usually comes as a compressed file on a floppy disk. Over time the updates get bigger and, at a certain point, an update may not fit on a single floppy. This is why good compression is important in the case of software updates. The time it takes to compress and decompress the update is unimportant since these operations are typically done just once. Recently, software makers have taken to providing updates over the Internet, but even in such cases it is important to have small files because of the download times involved. 1.1: (1) ask a question, (2) absolutely necessary, (3) advance warning, (4) boiling hot, (5) climb up, (6) close scrutiny, (7) exactly the same, (8) free gift, (9) hot water heater, (10) my personal opinion, (11) newborn baby, (12) postponed until later, (13) unexpected surprise, (14) unsolved mysteries. 1.2: A reasonable way to use them is to code the five most-common strings in the text. Because irreversible text compression is a special-purpose method, the user may know what strings are common in any particular text to be compressed. The user may specify five such strings to the encoder, and they should also be written at the start of the output stream, for the decoder’s use. -
Parallel Performance and Energy Efficiency of Modern Video Encoders on Multithreaded Architectures
PARALLEL PERFORMANCE AND ENERGY EFFICIENCY OF MODERN VIDEO ENCODERS ON MULTITHREADED ARCHITECTURES R. Rodr´ıguez-Sanchez´ 1, F. D. Igual2, J. L. Mart´ınez3, R. Mayo1, E. S. Quintana-Ort´ı1 1Depto. de Ingenier´ıa y Ciencia de Computadores, Universidad Jaume I (UJI), Castellon,´ Spain e-mails: frarodrig,mayo,[email protected] 2 Depto. de Arquitectura de Computadores y Automatica,´ Universidad Complutense de Madrid, Madrid, Spain e-mail: fi[email protected] 3Albacete Research Institute of Informatics, University of Castilla-La Mancha, Albacete, Spain e-mail: [email protected] ABSTRACT improve the encoding efficiency by introducing new tools or by improving the existing ones. In this paper we evaluate four mainstream video encoders: H.264/MPEG-4 Advanced Video Coding, Google’s VP8, Previous comparative analyses of video encoders mainly High Efficiency Video Coding, and Google’s VP9, studying focus on execution time and encoding efficiency. However, conventional figures-of-merit such as performance in terms of the considerable levels of hardware parallelism in current encoded frames per second, and encoding efficiency in both multicore servers, combined with the support for significant PSNR and bit-rate of the encoded video sequences. Addition- thread-level concurrency in these architectures, clearly asks ally, two platforms equipped with a large number of cores, for a detailed evaluation of the parallelism of modern video representative of current multicore architectures for high-end encoders. In particular, the number of threads/cores employed servers, and equipped with a wattmeter allow us to assess the in video encoders in general affects the execution time, but quality of these video encoders in terms of parallel scalability may also influence the encoding efficiency more subtlety, and energy consumption, which is well-founded given the as some encoding dependencies can be broken in a parallel significant levels of thread concurrency and the impact of the execution. -
Efficient Multi-Bitrate Hevc Encoding for Adaptive Streaming
EFFICIENT MULTI-BITRATE HEVC ENCODING FOR ADAPTIVE STREAMING Deepthi Nandakumar, Sagar Kotecha, Kavitha Sampath, Pradeep Ramachandran, Tom Vaughan MulticoreWare Inc. ABSTRACT Adaptive bitrate streaming is a critical feature in internet video that significantly improves the viewer experience by customizing video stream quality to the viewer device's capability and connectivity. Encoding the source content at multiple quality tiers or bitrates is extremely demanding for post-production houses, studios, and content delivery networks. This paper describes an intelligent multi-bitrate encoder, based on the High Efficiency Video Coding (HEVC)/H.265 standard that encodes a single title to multiple bitrates at significant performance gains and no compression efficiency loss, as compared to standalone single bitrate encoder instances. We first describe the threading infrastructure of x265, and demonstrate its ability to dynamically adapt to varying degrees of parallelism in hardware. We then describe the key architectural design of a multi-bitrate encoder, including thread synchronization challenges across encoder instances. We also discuss the analysis data shared across different quality tiers, that is carefully chosen to eliminate loss of compression efficiency compared to a single bitrate encoder instance. Finally, we show the high performance gains achieved by the multi-encoder, and demonstrate the feasibility of simultaneous encoding to multiple bitrates with negligible loss of compression efficiency. INTRODUCTION Over-The-Top (OTT) content streaming is poised to grow exponentially in the coming years, driven by the consumer’s need for a rich and high quality viewing experience. Recent projections indicate that Internet delivery of video will consume 80 to 90% of all Internet bandwidth by the year 2019 [1] [2]. -
An Overview of Emerging Video Coding Standards
[STANDARDS] Ticao Zhang and Shiwen Mao Dept. Electrical & Computer Engineering, Auburn University Editors: Michelle X. Gong and Shiwen Mao AN OVERVIEW OF EMERGING arious industrial studies and reports have predicted the drastic increase of video traffic VIDEO CODING in the Internet [1] and wireless networks [2]. Today’s popular video coding standards, such as H.264 Advanced video STANDARDS coding (AVC), are widely used in video storage and transmission systems. With the explosive growth of video traffic, it has been Today’s popular video coding standards, such as H.264/AVC, are widely recognized that video coding technology used to encode video into bit streams for storage and transmission. is crucial in providing a more engaging With the explosive growth of various video applications, H.264/AVC experience for users. For users that are often may not fully satisfy their requirements anymore. There is an increasing restricted by a limited data plan and dynamic wireless connections, high-efficiency video demand for high compression efficiency and low complexity video coding standards are essential to enhance coding standards. In this article, we provide an overview of existing their quality of experience (QoE). On the and emerging video coding standards. We review the timeline of the other hand, network service providers (NSP) development of the popular H.26X family video coding standards, and are constrained by the scarce and expensive wireless spectrum, making it challenging introduce several emerging video coding standards such as AV1, VP9 to support emerging data-intensive video and VVC. As for future video coding, considering the success of machine services, such as high-definition (HD) video, learning in various fields and hardware acceleration, we conclude this 4K ultra high definition (UHD), 360-degree article with a discussion of several future trends in video coding. -
State of the Art and Future Trends in Data Reduction for High-Performance Computing
DOI: 10.14529/jsfi200101 State of the Art and Future Trends in Data Reduction for High-Performance Computing Kira Duwe1, Jakob L¨uttgau1, Georgiana Mania2, Jannek Squar1, Anna Fuchs1, Michael Kuhn1, Eugen Betke3, Thomas Ludwig3 c The Authors 2020. This paper is published with open access at SuperFri.org Research into data reduction techniques has gained popularity in recent years as storage ca- pacity and performance become a growing concern. This survey paper provides an overview of leveraging points found in high-performance computing (HPC) systems and suitable mechanisms to reduce data volumes. We present the underlying theories and their application throughout the HPC stack and also discuss related hardware acceleration and reduction approaches. After intro- ducing relevant use-cases, an overview of modern lossless and lossy compression algorithms and their respective usage at the application and file system layer is given. In anticipation of their increasing relevance for adaptive and in situ approaches, dimensionality reduction techniques are summarized with a focus on non-linear feature extraction. Adaptive approaches and in situ com- pression algorithms and frameworks follow. The key stages and new opportunities to deduplication are covered next. An unconventional but promising method is recomputation, which is proposed at last. We conclude the survey with an outlook on future developments. Keywords: data reduction, lossless compression, lossy compression, dimensionality reduction, adaptive approaches, deduplication, in situ, recomputation, scientific data set. Introduction Breakthroughs in science are increasingly enabled by supercomputers and large scale data collection operations. Applications span the spectrum of scientific domains from fluid-dynamics in climate simulations and engineering, to particle simulations in astrophysics, quantum mechan- ics and molecular dynamics, to high-throughput computing in biology for genome sequencing and protein-folding. -
Appendix a Information Theory
Appendix A Information Theory This appendix serves as a brief introduction to information theory, the foundation of many techniques used in data compression. The two most important terms covered here are entropy and redundancy (see also Section 2.3 for an alternative discussion of these concepts). A.1 Information Theory Concepts We intuitively know what information is. We constantly receive and send information in the form of text, sound, and images. We also feel that information is an elusive nonmathematical quantity that cannot be precisely defined, captured, or measured. The standard dictionary definitions of information are (1) knowledge derived from study, experience, or instruction; (2) knowledge of a specific event or situation; intelligence; (3) a collection of facts or data; (4) the act of informing or the condition of being informed; communication of knowledge. Imagine a person who does not know what information is. Would those definitions make it clear to them? Unlikely. The importance of information theory is that it quantifies information. It shows how to measure information, so that we can answer the question “how much information is included in this piece of data?” with a precise number! Quantifying information is based on the observation that the information content of a message is equivalent to the amount of surprise in the message. If I tell you something that you already know (for example, “you and I work here”), I haven’t given you any information. If I tell you something new (for example, “we both received a raise”), I have given you some information. If I tell you something that really surprises you (for example, “only I received a raise”), I have given you more information, regardless of the number of words I have used, and of how you feel about my information. -
Towards Prediction Optimality in Video Compression and Networking
University of California Santa Barbara Towards Prediction Optimality in Video Compression and Networking A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Electrical and Computer Engineering by Shunyao Li Committee in charge: Professor Kenneth Rose, Chair Professor B. S. Manjunath Professor Shiv Chandrasekaran Professor Nikil Jayant March 2018 The Dissertation of Shunyao Li is approved. Professor B. S. Manjunath Professor Shiv Chandrasekaran Professor Nikil Jayant Professor Kenneth Rose, Committee Chair February 2018 Towards Prediction Optimality in Video Compression and Networking Copyright c 2018 by Shunyao Li iii To my beloved family iv Acknowledgements The completion of this thesis would not have been possible without the support from many people. I would like to thank my advisor, Prof. Kenneth Rose, for his guidance and support throughout the entire course of my doctoral research. He always encourages us to think about problems from the fundamental theory of signal processing, and to understand deeply the reasons behind the experiments and observations. He also gives us enough freedom and support so that we can explore the topics that we are interested in. I enjoy every constructive and inspiring discussion with him, and am genuinely grateful for developing a solid, theoretical and critical mindset under his supervision. I would also like to thank Prof. Manjunath, Prof. Chandrasekaran and Prof. Jayant for serving on my doctoral committee and providing constructive suggestions on my research. The research in this dissertation has been partly supported by Google Inc, LG Electronics and NSF. Thanks to our sponsors. I thank all my labmates for the collaborations and discussions. -
Region Based X-Ray Image Retrieval Using Transform Techniques *Dr
IJRECE VOL. 3 ISSUE 3 JULY-SEPT. 2015 ISSN: 2393-9028 (PRINT) | ISSN: 2348-2281 (ONLINE) Region Based X-Ray Image Retrieval using Transform Techniques *Dr. Ch. Raja *Associate Professor, Department of ECE, MGIT, Hyderabad, India. Abstract - Region Based Medical Image Retrieval (RBMIR) time of the search algorithm while extracting similar became popular aspect in Content Based Medical Image looking images from database [1].Therefore retrieval Retrieval (CBMIR) domain. Locally computed visual algorithm should compute optimal and minimal attributes attributes of a radiographic image has significant role in that better represent the images. This speeds up the retrieval retrieving the similar images from databases when process and results in faster extraction of similar images compared with globally computed features and this is one of from database. the prime aspects in making clinical decisions. Better X-Ray medical images are rich in textural representation, disease identification can be made by finding images of the compared to intensity and shape attributes, texture attributes same modality of an anatomic region. This obviously represent these images in a better way. According to the improves the healthcare system efficiency. X-Ray images survey of [5] and the work done in [2] textural features are best described in textural distributions compared to computed in transformed domain shown superior retrieval shape and intensity. The texture attributes computed from performance over spatially extracted attributes. Based on transformed domains shown superior performance over that in this work features extracted by transforming the spatially computed features. In this paper we proposed a image with Discrete Sine Transform (DST), Discrete Cosine novel approach for RBMIR by computing the region wise Transform (DCT), Discrete Fourier Transform (DFT) and visual attributes from four transformed domains viz.