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Input Based Dynamic Reconfiguration of Approximate Arithmetic Units for Video Encoding
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Input-Based Dynamic Reconfiguration of Approximate Arithmetic Units for Video Encoding

Category : VLSI


Sub Category : VLSI with MATLAB


Project Code : ITVL38


Project Abstract

The field of approximate computing has received significant attention from the research community in the past few years, especially in the context of various signal processing applications. Image and video compression algorithms, such as JPEG, MPEG, and so on, are particularly attractive candidates for approximate computing, since they are tolerant of computing imprecision due to human imperceptibility, which can be exploited to realize highly power-efficient implementations of these algorithms. However, existing approximate architectures typically fix the level of hardware approximation statically and are not adaptive to input data. For example, if a fixed approximate hardware configuration is used for an MPEG encoder (i.e., a fixed level of approximation), the output quality varies greatly for different input videos. This paper addresses this issue by proposing a reconfigurable approximate architecture for MPEG encoders that optimizes power consumption with the goal of maintaining a particular Peak Signal-to-Noise Ratio (PSNR) threshold for any video. Toward this end, we design reconfigurable adder/subtractor blocks (RABs), which have the ability to modulate their degree of approximation, and subsequently integrate these blocks in the motion estimation and discrete cosine transform modules of the MPEG encoder. We propose two heuristics for automatically tuning the approximation degree of the RABs in these two modules during runtime based on the Characteristics of each individual video. Experimental results show that our approach of dynamically adjusting the degree of hardware approximation based on the input video respects the given quality bound (PSNR degradation of 1%–10%) across different videos while achieving a power saving up to 38% over a conventional non-approximated MPEG encoder architecture. Note that although the proposed reconfigurable approximate architecture is presented for the specific case of an MPEG encoder, it can be easily extended to other DSP applications.

 

EXISTING SYSTEM

PROPOSED SYSTEM

EXISTING CONCEPT:

         There are multiple ways of setting the hard threshold for the output PSNR, which determines whether the quality of a video is acceptable or not. For the sake of simplicity, it is assumed that either the absolute PSNR or the  Percentage change in PSNR serves as a faithful yardstick for evaluating the quality  of videos outputted by the approximated MPEG encoder

 

PROPOSED CONCEPT:           

          An adaptive bit masking method is proposed in, where the authors propose to truncate the pixels of the current and previous frames required for ME  depending  upon the quantization step. A coarse-grained input truncation is applicable only to the specific case of ME and gives unsatisfactory results for other blocks, such as discrete cosine transform (DCT), which requires a finer regulation over error.

EXISTING TECHNIQUE:

         DCT

PROPOSED TECHNIQUE:

         DMFA

TECHNIQUE DEFINITION:

         The transform is orthogonal, we can always find its  Inverse, and the kernel matrix of the inverse transform is obtained by just transposing the kernel matrix of the forward transform. This feature of inverse transform could be used to compute the forward and inverse DCT by similar computing structures

TECHNIQUE DEFINITION:

·         Dual-mode FA (DMFA) cell in which each FA cell can operate either in fully accurate or in some approximation mode depending on the state of the control signal APP. A logic high value of the APP signal denotes that the DMFA is operating in the approximate mode

DRAWBACKS:

         Inaccuracy

         Prudent to be fail

         Complex to design

ADVANTAGES:

         A Proposed reconfigurable approximate architecture for the MPEG encoders that optimize power consumption while maintaining output quality across different input videos.


 
 
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