With today’s looming global climate crisis, there is also added pressure to become more environmentally responsible.
. The implications are potentially disastrous for climate change as more electronic devices are produced, each with its own carbon footprint, along with air, soil and groundwater pollution.
A move toward software-driven, hardware-accelerated architectures enables future technology enhancements without requiring hardware upgrades. This is an important step toward increasing technology lifespans without generating unnecessary waste.We’re at the proverbial crossroads, presented with opportunities for data center efficiency to both worsen and potentially improve. Data will continue to grow rapidly for almost every organization on the planet.
We’re also entering a new era in AI that relies on large language models to improve NLP accuracy . These new AI models will comprise training, analysis and inference, using up to trillions of parameters that place an increased burden on servers and other infrastructure.Focus on efficient data management and fast performance, including IO throughput.
Finally, you may be concerned about the heat generated in your data center by accelerated computing for AI workloads. Note that several prominent organizations, including Equinix and Meta, have begun running their data centers at—roughly 10 degrees above the industry average. Investigate whether you can increase your data center temperature by even a few degrees for substantial savings on cooling costs.
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