Analyzing the Energy Crisis – and Opportunities – in Computing

Analyzing the Energy Crisis – and Opportunities – in Computing

By: Abhishek Kapoor, Vice President of Sales

As the world becomes more connected, the demand for energy to support computing infrastructure continues to skyrocket. From data centers powering the internet and the smartphones in our pockets to the smart Internet of Things (IoT) automation around us, the need for greater computation is soaring. With this insatiable need for performance and computation, combined with a scarcity of energy, we are at a pivotal moment: energy is becoming the limiting factor in how much computation we can afford.

Year over year, the semiconductor industry has pushed the limits of performance, but the energy issue remains unsolved. This energy limitation hinders our ability to exploit the full potential of ubiquitous computing—anywhere, anytime. It also limits our ability to explore new use cases and innovations, hindering potential economic growth.

The energy crisis in computing

When we think about major energy consumers in computing, data centers typically come to mind first. Driven by the need for cloud computing and artificial intelligence (AI), energy consumed by data centers is expected to increase by nearly 450%, making it almost 9% of all US electricity by 2030.

While modern data centers serve as the backbone of our digital economy, their appetite for energy poses significant challenges in terms of cost and scalability. However, the real bottleneck for computational capacity and business potential lies at the edge—within the realms of the Internet of Things (IoT), wearables, and small devices.

These edge devices operate in energy-constrained environments where sustaining a power source is often unfeasible. Instead, they rely on batteries or energy harvesting. Frequently deployed in remote locations with limited human oversight, these devices are essential for monitoring and managing critical infrastructure that underpins our economy, including oil and gas pipelines, electric utility poles, bridges, telecommunications equipment, and more

As the demand for edge automation and computational capabilities continues to rise, the mainstream processor industry has largely prioritized performance over energy efficiency for decades. Yet, we need a radical transformation in energy efficiency. Addressing this challenge is crucial for unlocking the full potential of edge computing and ensuring a sustainable future for our digital landscape.

At the Edge: Processing Options and Challenges

Historically, processing at the edge has boiled down to three main options:

• High-Performance, Low-Efficiency Processors: These include lower-powered variants of traditional high-performance chips like GPUs, FPGAs, and accelerators. While they deliver significant computational power, their energy demands necessitate a constant power source or frequent battery replacements. This reliance on continuous power not only increases costs but also hinders productivity and efficiency, severely limiting their potential for mass deployment.
• Higher-Efficiency, Lower-Performance Processors: Devices like traditional MCUs, MPUs, and ASICs are designed for lower power consumption, albeit at the cost of performance. They can operate on batteries for extended periods but are restricted to basic tasks. Often, they must transmit data to the cloud for more complex processing, incurring additional energy costs due to RF transmission and introducing delays that can be impractical in critical scenarios—such as real-time monitoring of oil pipelines.
• High-Performance, Limited Efficiency, Non-Programmable Processors: The trend toward AI/ML-trained accelerators and GPUs offers impressive performance, but at the expense of general-purpose programmability. Once deployed, these devices can only execute the specific functions for which they were trained, limiting their adaptability to evolving sensing needs at the edge. This inflexibility diminishes their long-term value and prevents organizations from maximizing their potential.

Due to these limitations, many businesses find themselves resorting to minimal or no computations at the edge. In some cases, this leads to reliance on manual labor to address operational needs—a costly and error-prone approach. For example, utility and infrastructure companies may spend millions dispatching crews to inspect every utility pole, bridge, highway, and dam. And when budgets are tight, maintenance frequency can be reduced or even skipped altogether.

Breakthrough energy efficiency and general-purpose programmability

Now, imagine a future where "smart sensors" can not only collect data but also make intelligent, real-time decisions. These sensors could be deployed anywhere, powered by small, cost-effective batteries, free from the limitations of traditional energy sources. By overcoming current computing and energy constraints, we could fully harness automation to drive efficiency and innovation.

A crucial aspect of this vision lies in enhancing energy efficiency of the processors, which can unlock new capabilities and enable devices to operate longer and smarter. General-purpose programmability is essential for this efficiency, allowing sensors to adapt to evolving needs and functionalities without being restricted by their initial programming. By improving both energy efficiency and programmability, we can significantly reduce costs and boost productivity.

This is where Efficient Computer comes into play. We are leading the charge with our groundbreaking energy-efficient general-purpose processor and effcc software compare. Built on an entirely new architecture, our latest E1© chip offers over 166x* more energy efficient than any other general-purpose chip on the market, while being fully software programmable to meet a wide range of computing needs.

‍

Finally, the industry can achieve the vision of true on-device intelligence on the edge, without being energy constrained.

Contact Efficient at sales@efficient.computer or https://www.efficient.computer/contact to schedule a demo with Efficient Computer, and let’s shape the future of computing—together!