Red Hat makes it a strategic priority to offer energy-efficient products, addressing the growing demand of our customers for sustainable IT solutions. Our efforts are driven by minimizing the increase in energy consumption of AI, cloud computing, and IT infrastructure.
Red Hat's solutions for energy efficiency
Red Hat focuses on open source technologies designed to improve energy efficiency across IT environments. This includes:
- AI optimization: With Red Hat AI, you have access to Red Hat AI Inference Server to optimize model inference across the hybrid cloud for faster, cost-effective deployments. Powered by vLLM, the inference server maximizes GPU utilization and enables faster response times, thereby reducing the computational resources and energy required for AI workloads.
- Virtualization: Red Hat OpenShift Virtualization consolidates multiple virtual machines (VMs) onto fewer physical servers, directly translating to lower energy consumption and increased hardware utilization.
- System monitoring: Red Hat Enterprise Linux (RHEL) supports performance Co-Pilot (PCP), which provides detailed, real-time visibility into system performance and energy usage, enabling customers to identify and address inefficiencies.
- Power monitoring: Power monitoring for Red Hat OpenShift provides detailed insights into power consumption, improving adoption of energy-aware computing within cloud-native ecosystems.
- Intelligent automation: Red Hat Ansible Automation Platform boosts operational efficiency, reducing system down times, and intelligently optimizing resource utilization, which all contributes to a lower carbon footprint and enhanced energy efficiency.
Supporting small language models (SLMs) for energy efficiency
InstructLab is an open source project that enhances large language models (LLMs) used in generative AI (gen AI), upgrading an LLM with less human input and fewer resources than retraining. One of the key aspects of InstructLab is its focus on smaller, fine-tuned language models. This approach directly translates to improved energy efficiency compared to larger, more resource-intensive LLMs deployed by competitors.
Smaller language models require significantly less computational power for training and inference, leading to reduced energy consumption. InstructLab optimizes performance by tailoring SLMs to specific tasks or domains, enhancing efficiency, minimizing wasteful energy, and enabling models to run on lower-power CPUs as opposed to power-hungry GPUs. This lower energy consumption results in reduced operational costs, providing both financial benefits and support for sustainability goals.
Business benefits for customers
Red Hat's energy-efficient solutions offer significant benefits for enterprises, from reducing operational costs to helping achieve ambitious sustainability targets. By optimizing resource utilization and enhancing performance, these solutions also provide a crucial competitive advantage in today's market, which include:
- Reduced operational costs: By optimizing resource utilization and lowering energy consumption, Red Hat's solutions contribute to a significant reduction in the total cost of ownership (TCO) for IT infrastructure.
- Meeting sustainability and net-zero goals: Adopting energy-efficient solutions from Red Hat may help organizations make progress towards their energy efficiency goals.
- Improved performance: Red Hat's approach focuses on delivering enhanced application performance and responsiveness while optimizing resource utilization, leading to a more efficient IT environment.
- Competitive advantage: Embracing sustainable IT practices through Red Hat's offerings allows businesses to gain a competitive edge by appealing to their environmentally conscious customers and stakeholders.
Partnership initiatives
Red Hat and SoftBank have collaborated on Artificial Intelligence Radio Access Network (AI-RAN) to optimize power consumption in datacenters powering AI applications and vRAN. This project integrates Kepler, an open source project founded at Red Hat, into SoftBank's AI and Telecom Radio Access System (AITRAS) platform. Kepler monitors power consumption at the application and cluster level, allowing for more dynamic optimization of workload placement based on real-time energy usage, renewable energy availability, and carbon intensity. Additionally, Red Hat is collaborating with Orange to accelerate telco cloud transformation and services softwarization. This involves Orange consolidating on Red Hat OpenShift and Red Hat Ansible Automation Platform to build a cloud-native infrastructure. This collaboration achieves a reduced carbon footprint by optimizing hardware setup, reusing existing equipment, and taking advantage of power monitoring capabilities in Red Hat OpenShift.
Conclusion
As industries accelerate their digital transformation journeys, the demand for energy-efficient solutions will only grow. Red Hat is uniquely equipped to help our customers meet their needs with open source innovation, AI integration, and a strong commitment to sustainability.
In the evolving world of IT, energy efficiency isn’t just a trend—it’s a strategic advantage, and Red Hat is leading the charge.
关于作者
Dan Schnitzer is the Global Sustainability Lead for Red Hat where he is working to embed a culture of holistic sustainability throughout the organization and designing and implementing a plan to reach Red Hat’s 2030 climate ambition. Dan supports Red Hat’s engineering, products, RFP and sales teams to see how Red Hat products can provide energy savings opportunities for Red Hat’s customers; empowering them with data, cost-savings and support in achieving their own environmental goals.
Prior to Red Hat, Dan was the Director of Construction and Sustainability for Durham Public Schools, the Director of Sustainability & Capital Projects for the Chapel Hill-Carrboro City School District and the founding Director of Sustainability & Operations for the Academy for Global Citizenship in Chicago. Dan has consulted on sustainability with institutions internationally including Japan, Uganda and Germany. Dan believes that massive change is necessary and possible.
