In the rapidly evolving data center landscape, optimizing energy consumption has become a key focus. In this blog post, we delve into the intricacies of power consumption and explore the economics of his three main components: CPU, GPU, and AI accelerator, and how implementing proteanTecs power reduction solutions changes both power efficiency and compute power. I’ll try to figure out what to do.
The importance of power optimization in data centers
Cloud-scale data center requirements are pushing the boundaries of infrastructure performance and resiliency, highlighting power optimization as a key factor. As data centers continue to expand to meet the demands of an increasingly digital world, efficient use of electricity is not only a cost-saving strategy, but also a fundamental approach to sustainability and environmental responsibility. .
Why power optimization is essential:
- Cost efficiency: Data centers have huge energy demands, so optimizing power usage has a direct impact on operational costs. Efficient power consumption translates into significant savings for data center operators, improving the overall economics of these facilities.
- Environmental impact: Beyond financial considerations, power optimization aligns with environmental sustainability goals. Reducing the carbon footprint of data centers has become a priority at a time when the environmental impact of technology is being seriously examined.
Beyond energy efficiency: Improving infrastructure performance
Reducing the power consumption of individual devices within a data center not only contributes to improved energy efficiency, but is also key to improving infrastructure performance. By lowering the power demand of each system, the available power increases proportionately within the overall data center budget. This surplus power can be strategically reallocated, allowing for improved system utilization. Effectively, per-device power optimization strengthens the data center infrastructure to handle more computational tasks without exceeding power constraints. This dynamic balancing ensures a responsive and efficient data center, where each watt of device power saved contributes to increased capacity to meet computing demands.
However, achieving effective power optimization in data centers is not without its challenges, including:
- Dynamic workload: Data centers host a wide variety of applications with different workloads. Optimizing power across dynamically changing workloads requires advanced technology that can adapt to fluctuations in demand.
- Aging infrastructure: Many data centers have legacy infrastructure that may not inherently be designed for optimal power efficiency. Such infrastructure upgrades or renovations pose challenges in achieving comprehensive power optimization.
- Cooling requirements: Data centers generate a lot of heat, so cooling systems are essential. The equation is simple. The more power your device consumes, the more power you need to cool it. It’s a vicious cycle. Balancing the power consumption of IT equipment and the energy demands of cooling systems is a complex challenge in achieving overall efficiency. Companies strive to reduce power usage efficiency (PUE) to an optimized 1:1 ratio.
proteanTecs has introduced a solution for the complex task of power management in data centers. In response to challenges such as dynamic workloads, process variations, environmental factors, and aging effects, proteanTecs AVS Pro goes far beyond traditional adaptive voltage scaling (AVS) to reduce power consumption in mission mode. Provides a real-time, detailed data application to monitor usage. Method.
By employing on-chip agents that continuously monitor millions of logic paths in real-time, AVS Pro uniquely identifies the lowest margin for timing failure. This real-time resolution allows the system to dynamically adjust the supply voltage based on actual timing margins to optimize power consumption while ensuring error-free functionality. Unlike traditional AVS techniques that are limited by local on-chip sensors and emulators, AVS Pro’s margin agent addresses dynamic effects throughout the device’s lifetime.
AVS Pro not only leverages excess margin to enable power and performance optimization, but also protects against timing failures, redefining the balance between reliability, efficiency, and performance. Proven on multiple customer systems, proteanTecs AVS Pro has demonstrated power savings in the range of 9-14%. For data centers and cloud providers, this translates to millions of dollars in annual savings.
Redefining the economics of power
Let’s take a closer look at the financial impact of reducing system power and the impact on infrastructure utilization. Taking into account the above savings, the following model provides a comprehensive framework for evaluating both the cost and operational impact of a data center. [1]
Increased power across CPU, GPU, and AI accelerators.
CPU
Understand the baseline: Prior to incorporating proteanTecs, the data center operated with the following assumptions for CPU:
- Power consumption (kWh): 0.15
- Occupancy rate: 60%
- PUE: 1.3
- Total power per CPU (kWh): 0.117
Considering 500,000 CPUs and a power cost of 0.10 kW/hour, the annual power cost is $51,246,000.
Impact: Introducing ProteanTecs technology resulted in 11% power savings per CPU. This equates to a cost savings of $5,637,060 per year.
Improved transaction performance: Beyond cost savings, the power reduction per CPU could result in an additional 1.9 billion transactions per second (TPS).
GPU
Understand the baseline: Before proteanTecs, the modeled GPU infrastructure consisted of:
- Power consumption (kWh): 0.35
- Occupancy rate: 60%
- PUE: 1.3
- Total power per GPU (kWh): 0.273
Considering 500,000 GPUs and a power cost of 0.10 kW/hour, the annual power cost totals $119,574,000.
Impact: Implementing proteanTecs results in 10% power savings per GPU, representing a potential annual cost savings of $11,957,400 for the data center.
FPS enhancements: If the power reduction is channeled into higher utilization, we would expect to see an increase of 4 million frames per second (FPS) directly attributable to the GPU power reduction.
AI accelerator
Understand the baseline: The modeled AI accelerator setup initially had the following features:
- Power consumption (kWh): 0.2
- Occupancy rate: 60%
- UE: 1.3
- Total power (kWh) per AI accelerator: 0.156
Considering 500,000 AI accelerators and a power cost of 0.10 kW/hour, the annual power cost reaches $68,328,000.
Impact: The integration of proteanTecs can result in 12% power savings per AI accelerator, which can equate to $8,199,360 in annual data center cost savings.
Rapid increase in inference speed: When it comes to inference, we can witness a significant increase of 12.3 billion inferences per second (Inf/s) due to power reduction.
This case study highlights the transformative impact across data center electronics, including CPUs, GPUs, and AI accelerators. Beyond significant cost savings, this technology enables increased computational power and demonstrates a paradigm shift in data center efficiency.
OPEX to CAPEX
Reducing energy consumption per device not only provides immediate power/performance benefits, but also opens the door to countless additional benefits, creating a ripple effect throughout your infrastructure. One notable benefit is the extended lifespan of the system. Optimizing power usage reduces wear and tear on hardware components, increasing their longevity and mean time to failure (MTTF). This helps reduce maintenance costs and capital expenditures (CAPEX) by deferring the need for hardware replacement. In today’s data center landscape, capital investment optimization is the most important strategy. Organizations are looking to move from traditional 3-4 year hardware replacement cycles to more sustainable 5-6 year cycles to maximize service life and strengthen the long-term viability of their infrastructure. That’s what I’m aiming for.
conclusion
AVS Pro, part of proteanTecs power reduction solutions, represents a significant advancement in power management technology and addresses the limitations of existing methods. Real-time monitoring of timing margins and application-specific workloads provides a comprehensive solution to optimize power consumption while maintaining reliability. Benefits include reduced dynamic power, protection against timing failures, and the ability to adapt to changing conditions over the life of the device. The integration of proteanTecs AVS Pro is a strategic move to achieve superior power efficiency and performance in the face of evolving challenges in data center power consumption.
Addressing power optimization in data centers is a critical step in shaping a more sustainable and efficient future for the information technology environment. Despite the challenges and limitations, the progress achieved exemplifies the potential for significant improvement.
proteanTecs AVS Pro is proven and used in ICs by leading chip manufacturers, hyperscale cloud vendors, and mobile brands. This solution is integrated into advanced process nodes down to 3nm.
[1] The model provides estimates based on assumptions. Actual results may vary depending on specific hardware configuration, workload, usage patterns and data center environment.
