The MVP: A Highly-Integrated Video Compression Chip
`Robert J. Gove
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`Texas Instuments, Inc.
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`Dallas, Texas 75265
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`ABSTRACT
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`We introduce a new highly-integrated processing chip for performing a variety of
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`functions, however this chip is particularly well suited for video compression algorithms.
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`Applications include multimedia PCs, virtual reality 3D graphics, full-duplex
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`videoconferencing, HDTV, and color hardcopy. We have architected the Multimedia Video
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`Processor, or MVP, to provide a yet unattainable level ofperformance from a single chip,
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`although with the programmability typically found in today's general-purpose computers.
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`While advanced semiconductor design and process techniques have been used for its
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`design, the key to the advantage of this component lies in optimization of the architecture
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`for real-time video and graphics processing. This paper will analyze video compression
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`application requirements, describe the MVP architecture, and pose its potential as a very
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`capable solution for a wide range of markets.
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`INTRODUCTION
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`The computer and consumer video industries are pursuing varied paths to offer cost-
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`effective computing products which provide new forms of information and entertainment.
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`Products are emerging from cable TV delivery of interactive digital movies to digital mobile
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`offices. Digital compression and video processing at a reasonable cost are spurring this
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`revolution. While algorithm developments have been important, most of the enabling
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`advances lie in the availability of high—density memory and high-performance processing
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`ICs. With the pending general availability of the Multimedia Video Processor, or MVP, in
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`1994, a yet unattained level of digital signal processing performance will be available and
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`with all the flexibility of present day programmable computers. Standard-based video-
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`conferencing and playback of compressed digital video and audio (using PX64. IPEG or
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`MPEG "multi—standard" codecs systems) with a single MVP processor will be possible, as
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`well as codecs with yet-to-be-defined algorithms like model-based compression.
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`However, not only will the MVP support compression, it will also handle processing of
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`high-resolution video, full-motion video processing from sources like camcorders, digital
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`audio processing, hardcopy raster image processing, and 3D graphics, and all under
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`software control and generation. From this wide range of functions, we calculated that
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`several billion operations per second are required to provide video-based applications on
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`the desktop. Current and soon to appear desktop host processors like X86, Pentium,
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`Alpha, and MIPS do not have the computational power to meet these demands.
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`KEYS TO THE MVP ARCHITECTURE
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`The MVP's unique architecture and computational power enables users to integrate these
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`varied functions on a single processing component. The keys to obtaining both exceptional
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`processing speeds and fully-programmable features with the MVP include the use of:
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`(1) an fiicient parallel processing architecture,
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`(2) fast pixel processing tuned to image, video, and graphics processing,
`('0 imollinont finnffnl nr.'mm~m Amen fl...” rL.ymmLm f Hm nwahimnmva
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`(4) single-chip integration without slower chip-to-chip communications.
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`1068-0314/94 $3.00 © 1994 IEEE
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`Page 1 01°10
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`Samsung Exhibit 1006
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`PRIOR-ART_0010815
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`Page 1 of 10
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`Samsung Exhibit 1006
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`multiply and accumulate for various types of filtering operations. To obtain good image
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`quality at any channel rate and 30 frames per second, the image processor must compute
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`over 1.2 billion operations per second (BOPS).
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`The addition of audio compression (which requires highcr precision integer and possibly
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`floating point algorithms) and network communication, necessary for video conferencing
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`(G728 or G.71l, H.242, H.230, H.221), further increases the scope of computational
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`requirements. Reducing the system cost, we propose to include support in the architecture
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`for the required non—standard functions like color space conversion (YCrCb to RGB),
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`decimation of the source image to CIF resolution and variable scaling of the decompressed
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`sequence. Complete implementation of compression applications such as video-
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`conferencing requires over 2 BOPS of the programmable image processor.
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`ARCHITECTURE CHOICES
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`We considered several candidate parallel architectures for implementation of this single—chip
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`video processor [Gove-92, Guttag-92]. An architecture with a mix of dedicated and
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`programmable processors was initially evaluated, then subsequently discounted when no
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`single dominant function was found that was necessary almost all of the time. Besides, We
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`predicted that by the time the chip was completed, that a new important algorithm would
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`emerge. From the standpoint of loss of silicon efficiency by dedicated resources to any one
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`function (like a DCT), we felt compelled to seek a general-purpose well—balanced system
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`solution. Several other candidates existed, however the mix of algorithms and practical
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`implementation limitations focused us on SIMD and MIMD architectures. These differ by
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`the autonomy of the processors functions with MIMD -- a desirable feature for any data
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`dependent algorithm operating in parallel.
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`With MIMD desirable, the choice of a processor and memory interconnection architecture
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`remained. Pipelined, shared bus memory, communication port (mesh/array/hypercube),
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`and crossbar fully-shared memory were considered. Pipeline memory and processors
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`(systolic arrays) are typically used for video, however they're too restrictive in the sense
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`that one must a priori know the size of the memory and dynamics of the algorithm to
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`prevent data contention and processor stalls. With our varied needs, this would lead to
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`inefficiencies. A shared—bus memory structure would also have bottleneck problems with
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`highly variable instruction and data streams and moving of results from one processor to
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`the other. The n-way connected communication port requires a very ordered flow of data,
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`like a systolic or wavefront flow of data, or the application of a pixel per processor (not
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`practical in a single chip). This approach works for large arrays of simple processors
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`which can operate uniformly on images, however we wanted more complex processors
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`which could adapt
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`representations. The crossbar fully~shared memory is ideally suited to these needs,
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`minimizing contention, data movement and providing flexibility for many types of
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`In fact, since the crossbar operations at the processor instruction rates, this
`algorithms.
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`architecture can functionally emulate the other approaches (pipeline, shared bus...).
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`We not only wanted to provide this order of magnitude performance increase, but the goal
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`was to apply a traditional computer model of programmable processing and a large memory
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`to applications with integrated image, graphics, video and audio processing, or image
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`computing. As shown in Figure #2 titled "MVP System Architecture", replacing the
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`processing and memory pipeline of conventional video systems with the single video
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`processor and large memory system model yields tremendous application flexibility,
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`effect the system can re-configure itself with software from video conferencing to playing
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`CD movies, just as a PC would re-configure from a spreadsheet to a video game.
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`Page 4 Of 10
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`PRIOR-ART_0010818
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`Page 4 of 10
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`dependent algorithms like object feature matching or Huffman coding and also supporting
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`traditional data independent SIMD operations like convolution.
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`To prevent contention for memory or register access, a very wide instruction set in the
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`the programmer to produce highly-parallel optimized code. A performance penalty may
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`result if only one highly-serial task is performed continuously, however, the very nature of
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`image, video, graphics, and audio processing, with varied concurrent and complex
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`processing, prevents this from occurring. The MVP integrates more functions than ever
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`before into one chip, while avoiding the compromises of other architectures.
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`Detailed Architecture Description:
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`Figure #1, titled "MVP Block Diagram", shows the MVP chip architecture. The Master
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`Processor (MP) provides a RISC processor for simple user interface, sequential
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`processing, and orchestration of multiple concurrent tasks operating on the entire MVP.
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`The DSP Parallel Processors (PP), of which 4 will be designed in the first version of the
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`MVP, provide highly—optimized image/video/graphics/audio processing capabilities. The
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`Transfer Controller (TC) intelligently moves data and instructions on and off the MVP. All
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`of these processors are locally interconnected with a crossbar to 25 on-chip 2Kbyte SRAM
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`modules. Other features include dual video frame timing generators (VC) and JTAG test
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`and emulation circuits.
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`With five 32+bit programmable processors operating at one targeted state rate of SOMI-Iz
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`and numerous parallel operations performed in each processor, over 2 billion operations
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`per second result.
`In addition, 100 MFLOPS (fully IEEE-754) can occur. The peak data
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`transfer rate is then 400 MBytes/second, adequate for many video applications. The
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`internal bandwidth over the crossbar between on-chip memory and processors is 2.4
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`GBytes/second.
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`DSP PARALLEL PROCESSORS (PP)
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`The PP has many powerful features beyond those found in conventional DSPs. Practically
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`all video algorithms benefit from these features. Most of the features were added to permit
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`scalability within the PP to support many simple functions (like bit ops) in one cycle or
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`fewer operations with the same hardware at higher precision (like 32-bits). The following
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`describes the feature and advantage:
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`- 44 user registers:
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`- ease of programming/compiling and fast parallel functions.
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`- Single-cycle access into crossbar memory expands effective registers to 34K:
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`- flexibility.
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`0 Three-leveL no overhead instruction looping:
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`- programming flexibility and faster tight loops (usually 2030%)
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`- Double parallel transfer from memory with address update:
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`- most algorithms need two pixels loaded per cycle.
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`- Three-operand ALU arithmetic and logical operations:
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`- double speed correlation and windows support.
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`- Splitable mulfiply (8x8=l6 or 16x16=32):
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`— double speed pixel operations.
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`- Word/I-Ialfword/Byte multiple arithmetic:
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`- 4x on algorithms like motion estimation and 2x on fast DCTS.
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`- Flexible data path:
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`- masking, merging, rotating... for bit stream coding (like Huffman).
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`- General-purpose use of address adders:
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`PRIOR-ART_0010820
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`- Conditional operations prevent need for branching (and possible pipeline stalls):
`- adaptive algorithms will operate faster (like adaptive thresholdmg).
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`As a result, as many as 15 RISC operations will be performed in one PP cycle. When
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`multiplied by the number of FPS and added to the MP and FPU operations, a formidable
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`number results.
`In addition, since the C—compiler also influenced the architecture of the
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`PP, many of these features will automatically compile into fast cod -- many users of the
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`MVP will not need to understand the PP architecture to take advantage of its performance.
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`MASTER PROCESSOR (MP)
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`The MP is a general-purpose RISC processor with an integral IEEE-compatible floating-
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`point unit. A 32-bit instruction is accessed from a 4KByte instruction cache. Data loads
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`can be 8, 16, 32, or 64 bits from a 4KByte data cache or from any data module via the
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`crossbar. The MP has thirty-one 32-bit usable registers. Uncommon features include:
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`- Register files common to floating—point & integer operations.
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`° Scoreboard keeps track of result of loads and FPU, preventing use until updated.
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`- Addressing modes support optional updating of base-address register with
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`results of the address computation.
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`- Special FPU instruction permits new multiply. add/subt, & increment each cycle.
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`- Left-most and Right-most one logic.
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`- Both endians supported.
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`Since the MP was designed to efficiently execute C programs and has added hardware for
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`bitsueam processing, it performs exceptionally well as the controller and data interpretation
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`processor. The floating point capability accelerates and simplifies programming of high
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`precision applications like medical imaging and 3D graphics.
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`SHARED MEMORY & TRANSFER CONTROLLER (TC)
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`Much of the advantage of the MVP architecture lies in the memory and data I/O
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`architecture. Each processor and memory is fully interconnected through the crossbar and
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`switchable at instruction rates. With greater than 500 signal lines switching at nanosecond
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`the crossbarred memory architecture is only possible with single-chip
`speeds,
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`implementation. With adequate on-chip memory and the ability to reconnect the next
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`processor to the data memory, rather than moving the data to another memory, the data on-
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`chip is not required to move as often. In effect, the original requirement of billions of
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`bytes/second data transfer is reduced to only 100's of Mbytes/second. This model works
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`well as long as the algorithm uses localized regions of data (patches, blocks,
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`neighborhoods, rows...), each of which "fit" into the on-chip memory, and are accessed in
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`repeated or predictable patterns. While this usually occurs with image processing, an
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`extremely intelligent transfer controller was architected to aid in insuring the validity of this
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`assumption. The TC has numerous modes of transferring data on- or off—chip, each
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`optimized for a particular type of dataflow (block, patch, fat line, indexed or guided
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`patches...). Most importantly, the on-chip SRAM memory was architected with sufficient
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`size and modularity to permit double-buffering of data 1/0 on and off the chip, while the
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`on-chip processors access the other on-chip memory modules.
`In effect, practically no
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`overhead is required for video I/O. Many convenient methods were designed into the TC
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`to prioritize these accesses. In addition, we included support for most commodity memory
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`components (VRAM, SRAM, DRAM). Finally, we devised several methods to mitigate
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`any contention between the processors for a particular memory module. Both round-robin
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`and fixed-robin priority schemes are available to permit developers flexibility in structuring
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`Page 7 Of 10
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`PRIOR-ART_0010821
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`their algorithms to reduce contention. For the many image and video algorithms currently
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`developed for the MVP thus far, contention has not been a problem
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`Another advantage of the crossbar architecture is expandability. We can design many
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`different MVP chips, as a function of the number of PPs. We simply slice the architecture,
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`cutting or adding PPs and memory modules. Conceptually. the advantage of this approach
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`is that, with the same package and pin—out, several different performance and price points
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`can be used. A range of applications may require a range of different MVP chips.
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`Applications which require CCIR 601 studio quality video and/or multifunction processing
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`(graphics / audio) video) would most-likely require an MVP with 4 processors. On the
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`other hand, a more dedicated or single-function application like graphics may require
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`fewer PPs. In addition, if only limited resolution video (QCIF) processing is necessary,
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`again a small number of PPs could suffice. We anticipate various versions of the MVP in
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`the future.
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`VIDEO CONTROLLER (VC)
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`In addition, the MVP has two programmable timing controllers for generation of video and
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`other tinting signals. As an example, video frame grabbing and display requires may pixel,
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`horizontal, and vertical signals for synchronization of the external logic in the system. The
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`MVP has internal logic to generate those signals under program control, relieving the
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`system designer from design of external logic to perform those functions.
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`NEW DCT ALGORITHMS FOR COMPRESSION
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`SPEED-UP WITH USE OF A PROGRAMMABLE ARCHITECTURE
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`One advantage of the programmable compression chip is the optimization possible by
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`selecting the least computationally demanding DCT algorithm that will meet the accuracy
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`required of the application. For example, fast DCI’ algorithms like those of Lee and Chen
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`[Lee-84, Chen-77] have considerable advantage with respect to traditional matrix multiply
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`approaches (with a factor of 5 or more speedup). Seperability of the 2D DCT is generally
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`used for decomposition of DCTs (with successive processing of the individual rows &
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`columns of an image) . The size of the DCT directly influences the benefit of seperability,
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`however with the 8x8 DCTs of most standards, a definite speedup results. The Lee
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`algorithm tends to be easy to implement and achieve faster computation, although has
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`accuracy issues The Chen algorithm is harder to implement and is computational slower,
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`but with good accuracy. Depending on the available processing bandwidth, the encoder
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`can select an appropriate DCT or IDCT algorithm to perform the task.
`If errors result,
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`different coding decisions result and either lower SNRs or compression ratios occur.
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`In addition, we devised a "Truncated-IDCT" algorithm to utilize the advantages of a
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`programmable architecture. Since the DCT, quantizer and threholding operations seek to
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`minimize the population of selective frequency coefficients (for high compression),
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`statistically, most of the high frequency coefficients are zero valued. Therefore, the
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`conventional IDCI‘ will act on 8x8 matrixes with a high percentage of zero valued inputs.
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`We can then significantly reduce the amount of IDCT operations performed by not
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`executing the zero valued multiplies and adds (similar work has been reported[McMillan-
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`92]). This is only possible with software—based IDCTs.
`In implementation, the program
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`adaptively truncates the Sxl IDCT summation in the vertical direction based on the run-
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`length encoded input values. Further reductions by selecting 4x1 summation when
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`appropriate also shortens the process, although not as frequently. With this approach a
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`factor of 3 or more speed-up on 1DCIs will usually occur.
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`Page 8 of 10
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`PRIOR-ART_0010822
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`Page 8 of 10
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`TOOLS
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`223
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`Advances in video compression have been limited by the availability of tools to develop
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`software and hardware. With the MVP, TI offers a range of software tools and direct on-
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`chip support for in—circuit debug. A real—time executive, C++ compilers, algebraic
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`assembler, windowed high-level language debugger (with JTAG emulation hardware on
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`chip) and library of primitives/applications, all the tools familiar to computer application
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`developers, will now be available for development of video applications.
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`The software model for the MVP is based on two levels. The primary level includes the
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`Master Processor acting as a director and scheduler of the MVP's parallelism. The
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`Executive operates on the MP, performing those supervisory tasks. The Executive can
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`dispatch tasks for operation in pipeline, parallel or any other arrangement on any processor
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`within the MVP. Under that, a level which actually performs the tasks on each processor is
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`accessed by either: (1) a library of primitives, (2) application tools for programming in
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`assembly or (3) a high-level language compiler. Each of these methods have advantages,
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`with varying performance and skill level required to code the chip, as a function of the
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`particular application. Although nothing restricts the use of any processor as the master or
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`slave processor, only software convention.
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`COMPETING VIDEO COMPRESSION CHIP ARCHITECTURES
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`Several semiconductor companies have reported activity in video compression chip or chip
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`set solutions ([Bolton-93][Konstantinides-92]). Most chip manufacturers are proposing
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`hardwired or paramaterized architectures, without C—1evel programmability. Our MVP is
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`an exception. In addition, most of the other "programmable" approaches are based on an
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`architecture which integrates dedicated logic modules, like DCTs and Motion Estimators,
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`with only the controller programmable. This lirriits their efficiency since the silicon devoted
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`to those functions must always keep busy with those functions to justify their cost. On the
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`contrary the MVP architecture has no dedicated logic, permitting user balancing of silicon
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`based on the varied and dynamic computational demands of compression. Other
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`researchers have recently described simulations which support our position that universally
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`programmable architectures are competitive solutions when compared with dedicated or
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`hybrid architectures for video decompression (Mayer—93).
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`Many different architectures are proposed, in development, or currently available, however
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`none except the MVP has the flexibility nor computational performance to meet the
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`complete demands of truly integrated digital video on the desktop. including the complete
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`concert of real-time video & audio compression, with image & 3D graphics processing.
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`Not only compression and decompression, but system—level bit—stream control, video
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`scaling, error correction and even audio echo cancellation. Architecture limitations and
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`transistor counts limit other chips to subsets of these functions.
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`CONCLUSION
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`The MVP is a monolithic single—chip parallel processor that performs compression
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`processing, audio & video processing, 3D graphics and others, and even at the same time.
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`Over 2 billion operations are performed per second. This marriatic performance boost will
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`enable a wide range of new applications, including desktop interactive digital video.
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`Integrating fu1ly—programmable parallel DSP processors with a RISC processor on one
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`chip provides software flexibility and system adaptability. A new parallel architecture,
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`using a crossbar network to couple the processors and large on-chip SRAMs, and with
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`MIM.D (Multiple Instruction Multiple Data) operations, yields extremely high efficiency for
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`Page 9 of 10
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`PRIOR-ART_0010823
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`Page 9 of 10
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`most image, graphics, and video algorithms. Software tools like real-time executives,
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`assemblers and compilers all help bring a familiar computer programming model to
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`multidimensional signal processing. This new technology frees developers of compression
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`algorithms to optimize implementations of standard video & audio compression algorithms,
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`without the restrictions found in today's compression chips (those which are limited to
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`current interpretations or versions of the standards). In addition, algorithm developers can
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`implement future compression algorithms, without the difficulties of developing new chips
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`or adapting existing chips.
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`The MVP supports a wide range of open standards for video compression and image
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`computing The variation within each standard to promote creative and distinguishing
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`advantages in the market place and the constant urge to optimize the standard to a particular
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`range of markets, each work to prevent fixed hardware solutions. This programmable,
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`integrated solution gives flexibility to system designers to develop competitive algorithms
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`as well as adapt to emerging standards.
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`ACKNOWLEDGMENTS
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`The author wishes to thank Jeremiah Golston, Dr. Chris Read, and Dr. V. Venkateswar for
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`compression algorithm work relating to the MVP. In addition, thanks to the MVP Program
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`Manager, Walt Bonneau, for developing and motivating a "world-class" team. A special
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`thanks to my original co-MVP-architects, Keith Balmer, Karl Guttag, and Nick Ing-
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`Simmons. Finally, thanks to the entire "Team—MVP"!
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`REFERENCES
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`[Bolton-93] Bolton, M. "A Family of MPEG Video Encoder and Decoder Chips", IEEE
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