2020
DOI: 10.1109/tcsi.2020.2970923
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A Standalone FPGA-Based Miner for Lyra2REv2 Cryptocurrencies

Abstract: Lyra2REv2 is a hashing algorithm that consists of a chain of individual hashing algorithms, and it is used as a proofof-work function in several cryptocurrencies. The most crucial and exotic hashing algorithm in the Lyra2REv2 chain is a specific instance of the general Lyra2 algorithm. This work presents the first hardware implementation of the specific instance of Lyra2 that is used in Lyra2REv2. Several properties of the aforementioned algorithm are exploited in order to optimize the design. In addition, an … Show more

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Cited by 6 publications
(2 citation statements)
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“…A solitary exchange can make numerous yields, as happens when shipping off different locations, however any yield from a given exchange must be utilized as an information once in a square chain. Each ensuing reference is a twofold spend on an endeavor to spend twice [24]. In figure 2 shown the square construction, each square comprises of a few renditions of the square, the parent block hash, the Merkle tree root hash, timestamp, nBits, and Nonce [23].…”
Section: Methodsmentioning
confidence: 99%
“…A solitary exchange can make numerous yields, as happens when shipping off different locations, however any yield from a given exchange must be utilized as an information once in a square chain. Each ensuing reference is a twofold spend on an endeavor to spend twice [24]. In figure 2 shown the square construction, each square comprises of a few renditions of the square, the parent block hash, the Merkle tree root hash, timestamp, nBits, and Nonce [23].…”
Section: Methodsmentioning
confidence: 99%
“…The accelerator should be compared thoroughly to existing CPU and GPU-based miners for Cryptonight-Haven, hopefully showing increased throughput and/or energy efficiency. Finally, we also aim to compare to related work: FPGAbased miners were proposed for the ASIC-resistant PoW Lyra2REv2 [6], [7], Scrypt [8], and X16R [9].…”
Section: Future Workmentioning
confidence: 99%