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Accelerating PNG Encoding in Hardware

Authors: Cardoso, João F.; Sousa, José T. de;

Accelerating PNG Encoding in Hardware

Abstract

The objective of this work is to develop an Intellectual Property (IP) subsystem for Portable Network Graphics (PNG) encoders, capable of operating at 30 frames per second (FPS) with the Video Graphics Array (VGA) standard when embedded system on chip hardware. The developed IP subsystem comprises an ARM Cortex A9 CPU running at 667 MHz, coupled with a hardware IP module that implements the LZ77 algorithm, running at 100 MHz. The LZ77 compression step is the most time consuming of the tasks involved in the encoder when done in software, and the LZ77 hardware module accelerates its execution by a factor of 40 when compared with the software-only implementation running on the ARM system. The operation of the LZ77 IP is similar to that of a content- addressable memory, which is a well known technique to implement dictionaries in hardware. The proposed solution is implemented on an FPGA board, using a Xilinx Zynq 7000 device. Although the LZ77 IP has achieved 82.2 fps in VGA, thus exceeding the objective set for this work (30 fps) by roughly two times, the whole PNG encoder is only capable of achieving 3.5 fps, which is three times thrice as fast as its software-only implementation. For the encoder to be capable of operating at 30 fps, other functions need hardware acceleration as well, such as the input image filter, the entropy coder, and the bit stream packer. Additionally, the whole software base needs significant optimizations for that to be possible.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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