Fast Algorithm Designs of Multiple-Mode Discrete Integer Transforms with Cost-Effective and Hardware-Sharing Architectures for Multistandard Video Coding Applications

In this chapter, first we give a brief view of transform-based video coding. Second, the basic matrix decomposition scheme for fast algorithm and hardware-sharing-based integer transform design are described. Finally, two case studies for fast algorithm and hardware-sharing-based architecture designs of discrete integer transforms are presented, where one is for the single-standard multiple-mode video transform-coding application, and the other is for the multiple-standard multiple-mode video transform-coding application

HIGH-THROUGHPUT AREA-EFFICIENT INTEGER TRANSFORMS FOR VIDEO CODING

Ph.DDOCTOR OF PHILOSOPH

Tailored AVX2 Transform Kernels for Versatile Video Coding

Transform coding tools play an integral part in video codecs due to their substantial impact on coding efficiency. The latest video coding standard, Versatile Video Coding (VVC), makes the most of these tools by introducing new DST7, DCT8, and non-square transforms alongside the conventional DCT2 transform. This paper proposes optimized AVX2 kernels for all these transforms to speed up VVC coding. Unlike existing solutions, our kernels are specially tailored for each VVC transform type and block size. Accelerating our open-source uvg266 VVC encoder with the proposed kernels yields up to a 1.1× speedup under all intra (AI) coding condition without any coding overhead. Our implementations make forward DCT2 and DST7/DCT8 transforms 4.0× and 6.7× as fast as their respective scalar implementations in the VTM reference encoder. They also outpace the AVX2 kernels of the practical VVenC encoder by factors of 3.0× and 2.8×. The respective speedups rise up to 5.3×, 11.1×, 3.4×, and 3.0× with inverse transforms.Peer reviewe

Homogeneous and heterogeneous MPSoC architectures with network-on-chip connectivity for low-power and real-time multimedia signal processing

Two multiprocessor system-on-chip (MPSoC) architectures are proposed and compared in the paper with reference to audio and video processing applications. One architecture exploits a homogeneous topology; it consists of 8 identical tiles, each made of a 32-bit RISC core enhanced by a 64-bit DSP coprocessor with local memory. The other MPSoC architecture exploits a heterogeneous-tile topology with on-chip distributed memory resources; the tiles act as application specific processors supporting a different class of algorithms. In both architectures, the multiple tiles are interconnected by a network-on-chip (NoC) infrastructure, through network interfaces and routers, which allows parallel operations of the multiple tiles. The functional performances and the implementation complexity of the NoC-based MPSoC architectures are assessed by synthesis results in submicron CMOS technology. Among the large set of supported algorithms, two case studies are considered: the real-time implementation of an H.264/MPEG AVC video codec and of a low-distortion digital audio amplifier. The heterogeneous architecture ensures a higher power efficiency and a smaller area occupation and is more suited for low-power multimedia processing, such as in mobile devices. The homogeneous scheme allows for a higher flexibility and easier system scalability and is more suited for general-purpose DSP tasks in power-supplied devices

Data compression techniques applied to high resolution high frame rate video technology

An investigation is presented of video data compression applied to microgravity space experiments using High Resolution High Frame Rate Video Technology (HHVT). An extensive survey of methods of video data compression, described in the open literature, was conducted. The survey examines compression methods employing digital computing. The results of the survey are presented. They include a description of each method and assessment of image degradation and video data parameters. An assessment is made of present and near term future technology for implementation of video data compression in high speed imaging system. Results of the assessment are discussed and summarized. The results of a study of a baseline HHVT video system, and approaches for implementation of video data compression, are presented. Case studies of three microgravity experiments are presented and specific compression techniques and implementations are recommended

Energy efficient hardware acceleration of multimedia processing tools

The world of mobile devices is experiencing an ongoing trend of feature enhancement and generalpurpose multimedia platform convergence. This trend poses many grand challenges, the most pressing being their limited battery life as a consequence of delivering computationally demanding features. The envisaged mobile application features can be considered to be accelerated by a set of underpinning hardware blocks Based on the survey that this thesis presents on modem video compression standards and their associated enabling technologies, it is concluded that tight energy and throughput constraints can still be effectively tackled at algorithmic level in order to design re-usable optimised hardware acceleration cores. To prove these conclusions, the work m this thesis is focused on two of the basic enabling technologies that support mobile video applications, namely the Shape Adaptive Discrete Cosine Transform (SA-DCT) and its inverse, the SA-IDCT. The hardware architectures presented in this work have been designed with energy efficiency in mind. This goal is achieved by employing high level techniques such as redundant computation elimination, parallelism and low switching computation structures. Both architectures compare favourably against the relevant pnor art in the literature. The SA-DCT/IDCT technologies are instances of a more general computation - namely, both are Constant Matrix Multiplication (CMM) operations. Thus, this thesis also proposes an algorithm for the efficient hardware design of any general CMM-based enabling technology. The proposed algorithm leverages the effective solution search capability of genetic programming. A bonus feature of the proposed modelling approach is that it is further amenable to hardware acceleration. Another bonus feature is an early exit mechanism that achieves large search space reductions .Results show an improvement on state of the art algorithms with future potential for even greater savings

Approximate and timing-speculative hardware design for high-performance and energy-efficient video processing

Since the end of transistor scaling in 2-D appeared on the horizon, innovative circuit design paradigms have been on the rise to go beyond the well-established and ultraconservative exact computing. Many compute-intensive applications – such as video processing – exhibit an intrinsic error resilience and do not necessarily require perfect accuracy in their numerical operations. Approximate computing (AxC) is emerging as a design alternative to improve the performance and energy-efficiency requirements for many applications by trading its intrinsic error tolerance with algorithm and circuit efficiency. Exact computing also imposes a worst-case timing to the conventional design of hardware accelerators to ensure reliability, leading to an efficiency loss. Conversely, the timing-speculative (TS) hardware design paradigm allows increasing the frequency or decreasing the voltage beyond the limits determined by static timing analysis (STA), thereby narrowing pessimistic safety margins that conventional design methods implement to prevent hardware timing errors. Timing errors should be evaluated by an accurate gate-level simulation, but a significant gap remains: How these timing errors propagate from the underlying hardware all the way up to the entire algorithm behavior, where they just may degrade the performance and quality of service of the application at stake? This thesis tackles this issue by developing and demonstrating a cross-layer framework capable of performing investigations of both AxC (i.e., from approximate arithmetic operators, approximate synthesis, gate-level pruning) and TS hardware design (i.e., from voltage over-scaling, frequency over-clocking, temperature rising, and device aging). The cross-layer framework can simulate both timing errors and logic errors at the gate-level by crossing them dynamically, linking the hardware result with the algorithm-level, and vice versa during the evolution of the application’s runtime. Existing frameworks perform investigations of AxC and TS techniques at circuit-level (i.e., at the output of the accelerator) agnostic to the ultimate impact at the application level (i.e., where the impact is truly manifested), leading to less optimization. Unlike state of the art, the framework proposed offers a holistic approach to assessing the tradeoff of AxC and TS techniques at the application-level. This framework maximizes energy efficiency and performance by identifying the maximum approximation levels at the application level to fulfill the required good enough quality. This thesis evaluates the framework with an 8-way SAD (Sum of Absolute Differences) hardware accelerator operating into an HEVC encoder as a case study. Application-level results showed that the SAD based on the approximate adders achieve savings of up to 45% of energy/operation with an increase of only 1.9% in BD-BR. On the other hand, VOS (Voltage Over-Scaling) applied to the SAD generates savings of up to 16.5% in energy/operation with around 6% of increase in BD-BR. The framework also reveals that the boost of about 6.96% (at 50°) to 17.41% (at 75° with 10- Y aging) in the maximum clock frequency achieved with TS hardware design is totally lost by the processing overhead from 8.06% to 46.96% when choosing an unreliable algorithm to the blocking match algorithm (BMA). We also show that the overhead can be avoided by adopting a reliable BMA. This thesis also shows approximate DTT (Discrete Tchebichef Transform) hardware proposals by exploring a transform matrix approximation, truncation and pruning. The results show that the approximate DTT hardware proposal increases the maximum frequency up to 64%, minimizes the circuit area in up to 43.6%, and saves up to 65.4% in power dissipation. The DTT proposal mapped for FPGA shows an increase of up to 58.9% on the maximum frequency and savings of about 28.7% and 32.2% on slices and dynamic power, respectively compared with stat