Instruction re-encoding facilitating dense embedded code

Bonny, Talal; Henkel, Jörg

doi:10.1145/1403375.1403561

Cited by 7 publications

(2 citation statements)

References 16 publications

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“…(1) As a hardware-based technique we explicitly reduce the size of the decoding compression technique to improve the compression ratios in Bonny and Henkel [2008] and by compressing the lookup tables as we did in Bonny and Henkel [2007a]. In this work, we have refined both compression techniques and added new a compression technique, which combines both techniques together to achieve better compression results.…”

Section: Our Novel Contributionsmentioning

confidence: 99%

Huffman-based code compression techniques for embedded processors

Bonny

Henkel

2010

ACM Trans. Des. Autom. Electron. Syst.

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The size of embedded software is increasing at a rapid pace. It is often challenging and time consuming to fit an amount of required software functionality within a given hardware resource budget. Code compression is a means to alleviate the problem by providing substantial savings in terms of code size. In this article we introduce a novel and efficient hardware-supported compression technique that is based on Huffman Coding. Our technique reduces the size of the generated decoding table, which takes a large portion of the memory. It combines our previous techniques, Instruction Splitting Technique and Instruction Re-encoding Technique into new one called Combined Compression Technique to improve the final compression ratio by taking advantage of both previous techniques. The instruction Splitting Technique is instruction set architecture (ISA)-independent. It splits the instructions into portions of varying size (called patterns) before Huffman coding is applied. This technique improves the final compression ratio by more than 20% compared to other known schemes based on Huffman Coding. The average compression ratios achieved using this technique are 48% and 50% for ARM and MIPS, respectively. The Instruction Re-encoding Technique is ISA-dependent. It investigates the benefits of reencoding unused bits (we call them reencodable bits) in the instruction format for a specific application to improve the compression ratio. Reencoding those bits can reduce the size of decoding tables by up to 40%. Using this technique, we improve the final compression ratios in comparison to the first technique to 46% and 45% for ARM and MIPS, respectively (including all overhead that incurs). The Combined Compression Technique improves the compression ratio to 45% and 42% for ARM and MIPS, respectively. In our compression technique, we have conducted evaluations using a representative set of applications and we have applied each technique to two major embedded processor architectures, namely ARM and MIPS.

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Section: Our Novel Contributionsmentioning

confidence: 99%

Huffman-based code compression techniques for embedded processors

Bonny

Henkel

2010

ACM Trans. Des. Autom. Electron. Syst.

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“…Internet of Things (IoT) technology has attracted many researchers to dig more into it, therefore, many researchers merge IoT into their fields to exploit and evolve it over time [2][3]. Many research composed IoT servers on Field Programmable Gate Arrays (FPGAs) and system on chip SoC [4][5][6][7][8][9][10]. Although there is no single global definition, IoT can be defined as a set of devices that are connected as one single entity to collect, generate, and exchange data from each other, and perform some computing tasks without the interference of humans [11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Internet of Things (IoT) in solar energy: a bibliometrics analysis and global publications trends

AlMallahi,

Al Nassan,

Obaideen

et al. 2023

Energy Harvesting and Storage: Materials, Devices, and Applications XIII

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With the modernization of cities, the concept of the Internet of Things (IoT) is gaining popularity and becoming a vital source of smart developments. An added advantage of solar energy systems, IoT applications enable automatic and remote sensing, processing, and execution. IoT ensures that information is easily available and accessible from any location around the world. The IoT applications improve the visibility, scalability, and cost-effectiveness of solar energy generation and service. A bibliometric analysis of scientific publications in the field of solar PV and IoT applications was conducted using the Scopus database between the years 2011 and 2023. Many studies of technological development have been discovered, and some insights can still be approached in such a way that the practical implementation of photovoltaic solar systems is improved. Since 2013, there has been an increase in the rate of publications. The majority of these studies were conducted in India, and the most common IoT applications reported were in the fields of computer science and engineering. This article identifies knowledge gaps to inform the community, industry, and government officials about IoT research directions in the solar energy field.

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