Green Hardware Infrastructure for Algorithmic Trading

Green Hardware Infrastructure for Algorithmic Trading

연구 분야: Infrastructure

학회: European Conference on Artificial Intelligence

Every software needs hardware to be run on. Nowadays we encounter urgent need to mitigate the adverse effects of climate change. It prompted a paradigm shift towards the development of low carbon dioxide (CO2) emission hardware infrastructure. This scientific paper presents a thorough analysis of the current state of low CO2 emission hardware infrastructure, highlighting its significance in achieving sustainable and environmentally friendly technological advancements. The paper begins by highlighting the global greenhouse gas emissions and their significance in changing the climate. It emphasizes the crucial role of hardware infrastructure in this context, as the energy consumption and carbon footprint of data centers, communication networks, and other hardware-intensive systems continue to rise. Next, in the paper have been analyzed various strategies and technologies that have been developed to reduce CO2 emissions during computations. These include energy efficient designs, advanced cooling techniques, renewable energy integration, audits and controls, and optimization algorithms such modern AI tools. The advantages and limitations of each approach are discussed, with a focus on their potential for widespread adoption and scalability. The paper concludes by outlining the future prospects and challenges associated with low CO2 emission hardware infrastructure. It emphasizes the need for continued research and innovation to overcome existing barriers and accelerate the adoption of environmentally friendly hardware systems on a global scale.