Demystifying Crypto-Mining: Analysis and Optimizations of Memory-Hard PoW Algorithms

Abstract

Blockchain technology has become extremely popular, during the last decade, mainly due to the successful application in the cryptocurrency domain. Following the explosion of Bitcoin and other cryptocurrencies, blockchain solutions are being deployed in almost every aspect of transactional operations as a means to safely exchange digital assets between non-trusted parties. At the heart of every blockchain deployment is the consensus protocol, which maintains the consistency of the blockchain upon satisfying incoming transactions. Although many consensus protocols have been recently introduced, the most prevalent is Proof-of- Work, which scales the blockchain globally by converting the consensus problem to a competition based on cryptographic hash functions; a process called “mining”. The Proof-of- Work consensus protocol employs memory-hard algorithms in order to counteract ASIC or FPGA mining that may compromise the decentralization and democratization of the blockchain. Unfortunately, this leads to increased power consumption and scalability challenges since numerous processing units such as GPUs, FPGAs, and ASICs, are required to satisfy the ever-increasing operational requirements of blockchain deployments. In this paper, we perform an in-depth performance analysis and characterization of the most common memory-hard PoW algorithms running on NVIDIA GPUs. Motivated by our experimental findings, we apply a series of optimizations on Ethash algorithm, the consensus protocol of the Ethereum blockchain. The implemented optimizations accelerate performance by 14% and improve energy efficiency by 10% when executing on three NVIDIA GPUs. As a result, the optimized Ethash algorithm outperformed its fastest commercial implementation.