DNA technology for big data storage and error detection solutions: Hamming code vs Cyclic Redundancy Check (CRC)

There is an increasing need for high-capacity, highdensity storage media that can retain data for a long time, due to the exponential development in the capacity of information generated. The durability and high information density of synthetic deoxyribonucleic acid (DNA) make it an attractive and promising medium for data storage. DNA data storage technology is expected to revolutionize data storage in the coming years, replacing various Big Data storage technologies. As a medium that addresses the need for high-latency, immutable information storage, DNA has several potential advantages. One of the key advantages of DNA storage is its extraordinary density. Theoretically, a gram of DNA can encode 455 exabytes, or 2 bits per nucleotide. Unlike other digital storage media, synthetic DNA enables large quantities of data to be stored in a biological medium. This reduces the need for traditional storage media such as hard disks, which consume energy and require materials such as plastic or metals, and also often leads to the generation of electronic waste when they become obsolete or damaged. Additionally, although DNA degrades over thousands of years under non-ideal conditions, it is generally readable. Furthermore, as DNA possesses natural reading and writing enzymes as part of its biological functions, it is expected to remain the standard for data retrieval in the foreseeable future. However, the high error rate poses a significant challenge for DNA-based information coding strategies. Currently, it is impossible to execute DNA strand synthesis, amplification, or sequencing errors-free. In order to utilize synthetic DNA as a storage medium for digital data, specialized systems and solutions for direct error detection and correction must be implemented. The goal of this paper is to introduce DNA storage technology, outline the benefits and added value of this approach, and present an experiment comparing the effectiveness of two error detection and correction codes (Hamming and CRC) used in the DNA data storage strategy

Cyclic Redundancy Checking (CRC) Accelerator for the FlexCore Processor

A proven approach to increase performance of general-purpose processors is to add hardware accelerators. In its basic configuration, the FlexCore processor has a limited set of datapath units. But thanks to a flexible datapath interconnect and a wide control word, the FlexCore datapath is explicitly designed to support integration of special units that, on demand, can accelerate certain data-intensive applications. We present the integration of a versatile accelerator for several Cyclic Redundancy Checking (CRC) keys. Furthermore, we investigate the accelerator\u27s impact on processor execution time and energy efficiency, using the PowerStone CRC benchmark. Our evaluation shows that the accelerated 65-nm 2.7-ns FlexCore datapath is, for example, 86% more energy and cycle efficient than a datapath lacking the CRC accelerator. \ua9 2010 IEEE