Energy-efficient computing is especially important in the field of high-performance computing (HPC) on supercomputers. Therefore, automated optimization of energy efficiency during the execution of a compute-intensive program is desirable. In this article, a framework for the automatic improvement of the energy efficiency on NVIDIA GPUs (graphics processing units) using dynamic voltage and frequency scaling is presented. As application, the mining of crypto-currencies is used, since in this area energy efficiency is of particular importance. The framework first determines the energy-optimal frequencies for each available currency on each GPU of a computer automatically. Then, the mining is started, and during a monitoring phase it is ensured that always the most profitable currency is mined on each GPU, using optimal frequencies. Tests with different GPUs show that the energy efficiency, depending on the GPU and the currency, can be increased by up to 84% compared to the usage of the default frequencies. This in turn almost doubles the mining profit.

中文翻译：

---

基于频率缩放的自动调整对图形处理单元上区块链算法的能效

节能计算在超级计算机上的高性能计算（HPC）领域尤为重要。因此，需要在执行计算密集型程序期间自动优化能源效率。在本文中，介绍了使用动态电压和频率缩放自动提高 NVIDIA GPU（图形处理单元）能效的框架。作为应用，使用加密货币的挖掘，因为在该领域能源效率特别重要。该框架首先自动确定计算机每个 GPU 上每种可用货币的能量最佳频率。然后，开始挖掘，并在监控阶段确保始终使用最佳频率在每个 GPU 上挖掘最有利可图的货币。使用不同 GPU 的测试表明，与使用默认频率相比，能源效率（取决于 GPU 和货币）最多可提高 84%。这反过来几乎使挖矿利润翻了一番。