Achieving Consistent RTL Power Accuracy

Are you struggling to accurately estimate RTL power consumption early in your design process? RTL power estimation can be inaccurate due to the complexity of the designs, the various power domains, and the use of multiple tools in the design process. Designers can make effective power-performance-area tradeoffs early by using a holistic methodology that includes both architectural and micro-arc... » read more

Addressing Power Challenges In AI Hardware

Artificial intelligence (AI) accelerators are essential for tackling AI workloads like neural networks. These high-performance parallel computation machines provide the processing efficiency that such high data volumes demand. With AI playing increasingly larger roles in our lives—from consumer devices like smart speakers to industrial applications like automated factories—it’s paramount ... » read more

For AI Hardware, Power Optimization Starts With Software And Ends At Silicon

Artificial intelligence (AI) processing hardware has emerged as a critical piece of today’s tech innovation. AI hardware architecture is very symmetric with large arrays of up to thousands of processing elements (tiles), leading to billion+ gate designs and huge power consumption. For example, the Tesla auto-pilot software stack consumes 72W of power, while the neural network accelerator cons... » read more

Power Management Becomes Top Issue Everywhere

Power management is becoming a bigger challenge across a wide variety of applications, from consumer products such as televisions and set-top-boxes to large data centers, where the cost of cooling server racks to offset the impact of thermal dissipation can be enormous. Several years ago, low-power design was largely relegated to mobile devices that were dependent on a battery. Since then, i... » read more