Xiaoke Qin, Member, IEEE Chetan Murthy, and Prabhat Mishra, Senior Member, IEEE IEEE Transactions in VLSI Systems, March 2011 Presented by: Sidhartha Agrawal.

Slides:



Advertisements
Similar presentations
Machine cycle.
Advertisements

Chapter 1. Basic Structure of Computers
1 The 2-to-4 decoder is a block which decodes the 2-bit binary inputs and produces four output All but one outputs are zero One output corresponding to.
T.Sharon-A.Frank 1 Multimedia Compression Basics.
Logic Circuits Design presented by Amr Al-Awamry
Give qualifications of instructors: DAP
Performance Analysis and Optimization (General guidelines; Some of this is review) Outline: introduction evaluation methods timing space—code compression.
Data Compression Michael J. Watts
1 Lecture-2 CSIT-120 Spring 2001 Revision of Lecture-1 Introducing Computer Architecture The FOUR Main Elements Fetch-Execute Cycle A Look Under the Hood.
1 Asynchronous Bit-stream Compression (ABC) IEEE 2006 ABC Asynchronous Bit-stream Compression Arkadiy Morgenshtein, Avinoam Kolodny, Ran Ginosar Technion.
Compression & Huffman Codes
System Clock, clock speed, Word Length & Bus Width.
ENGS Assignment 3 ENGS 4 – Assignment 3 Technology of Cyberspace Winter 2004 Thayer School of Engineering Dartmouth College Assignment 3 – Due Sunday,
Compression & Huffman Codes Fawzi Emad Chau-Wen Tseng Department of Computer Science University of Maryland, College Park.
H.264 / MPEG-4 Part 10 Nimrod Peleg March 2003.
Object Oriented Analysis OOA. OOA Deliverables Static Object model –one single diagram Scenarios –set of diagrams Object Dictionary –one set of comprehensive.
The processor and main memory chapter 4, Exploring the Digital Domain The Development and Basic Organization of Computers.
1 Lecture-2 CS-120 Fall 2000 Revision of Lecture-1 Introducing Computer Architecture The FOUR Main Elements Fetch-Execute Cycle A Look Under the Hood.
The central processing unit and main memory chapter 4, Exploring the Digital Domain The Development and Basic Organization of Computers.
2015/7/12VLC 2008 PART 1 Introduction on Video Coding StandardsVLC 2008 PART 1 Variable Length Coding  Information entropy  Huffman code vs. arithmetic.
On Packetization of Embedded Multimedia Bitstreams Xiaolin Wu, Samuel Cheng, and Zixiang Xiong IEEE Transactions On Multimedia, March 2001.
Data dan Teknologi Multimedia Sesi 08 Nofriyadi Nurdam.
9/15/09 - L15 Decoders, Multiplexers Copyright Joanne DeGroat, ECE, OSU1 Decoders and Multiplexers.
Seok-Won Seong and Prabhat Mishra University of Florida IEEE Transaction on Computer Aided Design of Intigrated Systems April 2008, Vol 27, No. 4 Rahul.
High Throughput Compression of Double-Precision Floating-Point Data Martin Burtscher and Paruj Ratanaworabhan School of Electrical and Computer Engineering.
GFPC: A Self-Tuning Compression Algorithm Martin Burtscher 1 and Paruj Ratanaworabhan 2 1 The University of Texas at Austin 2 Kasetsart University.
296.3Page 1 CPS 296.3:Algorithms in the Real World Data Compression: Lecture 2.5.
Classifying GPR Machines TypeNumber of Operands Memory Operands Examples Register- Register 30 SPARC, MIPS, etc. Register- Memory 21 Intel 80x86, Motorola.
Survey on Improving Dynamic Web Performance Guide:- Dr. G. ShanmungaSundaram (M.Tech, Ph.D), Assistant Professor, Dept of IT, SMVEC. Aswini. S M.Tech CSE.
Chapter 1: Data Storage.
CIS250 OPERATING SYSTEMS Memory Management Since we share memory, we need to manage it Memory manager only sees the address A program counter value indicates.
A Decompression Architecture for Low Power Embedded Systems Lekatsas, H.; Henkel, J.; Wolf, W.; Computer Design, Proceedings International.
The LZ family LZ77 LZ78 LZR LZSS LZB LZH – used by zip and unzip
Codec structuretMyn1 Codec structure In an MPEG system, the DCT and motion- compensated interframe prediction are combined. The coder subtracts the motion-compensated.
CS430 © 2006 Ray S. Babcock LZW Coding Lempel-Ziv-Welch.
A New Operating Tool for Coding in Lossless Image Compression Radu Rădescu University POLITEHNICA of Bucharest, Faculty of Electronics, Telecommunications.
CS654: Digital Image Analysis Lecture 34: Different Coding Techniques.
Random Access Memory (RAM).  A memory unit stores binary information in groups of bits called words.  The data consists of n lines (for n-bit words).
Multi-media Data compression
SPIHT algorithm combined with Huffman encoding Wei Li, Zhen Peng Pang, Zhi Jie Liu, 2010 Third International Symposium on Intelligent Information Technology.
High Performance Embedded Computing © 2007 Elsevier Lecture 7: Memory Systems & Code Compression Embedded Computing Systems Mikko Lipasti, adapted from.
Compression techniques Adaptive and non-adaptive.
Page 1KUT Graduate Course Data Compression Jun-Ki Min.
©Brooks/Cole, 2003 Chapter 1 Introduction. ©Brooks/Cole, 2003 Figure 1-1 Data processor model This model represents a specific-purpose computer not a.
1 Hierarchical Parallelization of an H.264/AVC Video Encoder A. Rodriguez, A. Gonzalez, and M.P. Malumbres IEEE PARELEC 2006.
Re-configurable Bus Encoding Scheme for Reducing Power Consumption of the Cross Coupling Capacitance for Deep Sub-micron Instructions Bus Siu-Kei Wong.
1 SWE 423 – Multimedia System. 2 SWE Multimedia System Introduction  Compression is the process of coding that will effectively reduce the total.
Efficient Huffman Decoding Aggarwal, M. and Narayan, A., International Conference on Image Processing, vol. 1, pp. 936 – 939, 2000 Presenter :Yu-Cheng.
Decoder Chapter 12 Subject: Digital System Year: 2009.
Lab 4 HW/SW Compression and Decompression of Captured Image
Compression & Huffman Codes
Instruction Packing for a 32-bit Stack-Based Processor Witcharat Lertteerawattana and Prabhas Chongstitvatana Department of Computer Engineering Chulalongkorn.
Succinct Data Structures
Selective Code Compression Scheme for Embedded System
Exam 2 Review Two’s Complement Arithmetic Ripple carry ALU logic and performance Look-ahead techniques, performance and equations Basic multiplication.
Overview Instruction Codes Computer Registers Computer Instructions
Lempel-Ziv-Welch (LZW) Compression Algorithm
Huffman Coding, Arithmetic Coding, and JBIG2
Code Compression Motivation Efficient Compression
The Basic Organization of Computers T.Jeya M.Sc., M.Phil Assistant Professor, Department of CS, SAC Women’s College. Cumbum. Tamilnadu.
Chapter 1 Number System RGGP, Narwana.
ورود اطلاعات بصورت غيربرخط
How Computers Work Part 1 6 February 2008.
Number Systems Instructions, Compression & Truth Tables.
LOGIC Circuits.
Homework #2 Due May 29 , Consider a (2,1,4) convolutional code with g(1) = 1+ D2, g(2) = 1+ D + D2 + D3 a. Draw the.
Efficient Placement of Compressed Code for Parallel Decompression
Presentation transcript:

Xiaoke Qin, Member, IEEE Chetan Murthy, and Prabhat Mishra, Senior Member, IEEE IEEE Transactions in VLSI Systems, March 2011 Presented by: Sidhartha Agrawal

 Backgrounds Info (Quickly)  Previous Work  Major Contribution by present work ◦ Smart Placement ◦ Fast decompression for VLC ◦ Combine RLC and bit-mask based coding  Results  Conclusion  Question

Code Compression Overview Compressed Code (Memory) Decompression Engine Processor (Fetch and Execute) Application Program (Binary) Compression Algorithm Static Encoding (Offline) Dynamic Decoding (Online)

 Input: Input bitstream  Output: Compression Bitstream placed in memory  Step 1 : Divide input bitstream in Fixed size symbols  Step 2 : Perform Bitmask based pattern selection  Step 3 : Perform Dictionary Selection  Step 4 : Compress symbol into code sequence using bitmask and RLE  Step 5 : Perform decode aware placement of code

Marker Count Input Stream Without RLEWith RLE

 Definition: Power-Two n-bit Stream(“PT-n Stream”) is FLC stream of n-bit codes, where n is a power of two such as 2 0, 2 1, 2 2, and so on.

c

c

 The total number of unused bits Nw is less than (log 2 b + 2) * b  b is the memory bandwidth,  For b = 8 ◦ N w = 40

 Bit mask based Compression (BMC)  BMC with new dictionary selection (pBMC)  pBMC with RLE BMC pBMC ~ 4% pBMC + RLE ~ 10%

 Decompression Aware Code Placement  Use of RLE and BMC  Comments ◦ Very Comprehensive Paper(s)  Questions ◦ ???