Pushing AI capabilities towards the periphery necessitates the selection of appropriate processors and memory systems
In the rapidly evolving world of AI, the need for efficient and cost-effective edge solutions has never been more critical. Two industry leaders, Hailo and Micron, are collaborating to address this challenge, offering a promising combination of advanced AI processors and optimized memory solutions.
Hailo, a prominent AI silicon provider, offers breakthrough AI processors uniquely designed for high-performance deep learning applications on edge devices. Their Hailo-10H AI accelerator, designed specifically for edge devices such as smartphones, vehicles, and IoT devices, provides up to 40 TOPS (tera operations per second) of INT4 precision AI performance while consuming around 2.5 watts of power. This power efficiency allows it to run advanced large language models (LLMs), vision-language models (VLMs), and other generative AI tasks locally on-device without offloading to the cloud.
By handling the entire inference pipeline on the edge, Hailo-10H reduces latency, enhances data privacy, lowers operational costs, and avoids network dependency. Its integrated support for DDR memory interfaces ensures fast, efficient communication with memory, essential for handling large models under tight power and cost budgets.
Micron, on the other hand, provides low-power DDR memory solutions that complement AI co-processors like the Hailo-10H. Micron’s LPDDR technology offers high-speed, high-bandwidth data transfer without sacrificing power efficiency, ideal for edge AI applications. Micron’s LPDDR4X, for instance, is ideally suitable for Hailo's VPU as it delivers high performance, high-bandwidth data rates without compromising power efficiency. Moreover, Micron’s 1-beta LPDDR5X delivers 20% better power efficiency compared to LPDDR4X.
Managing AI at the edge introduces challenges beyond just having enough compute power. Memory performance, energy consumption, and cost are equally important considerations. Memory bandwidth and performance have not advanced at the same rate as compute power, creating a bottleneck. However, with the introduction of LPDDR4/4X and LPDDR5/5X, significant performance gains have been achieved. LPDDR5X, for example, doubles the performance of LPDDR4X.
The combination of Micron's LPDDR technology and Hailo's AI processors allows a broad range of applications, from industrial and automotive to enterprise systems. This partnership fosters cost-effective and scalable AI solutions for power- and cost-constrained sectors like automotive, smart home, industrial IoT, and mobile devices.
As the industry shifts towards more efficient compute architectures and specialised AI models for distributed, low-power applications, solutions like Hailo and Micron's are becoming increasingly relevant. Developers need to consider edge AI solutions that can support on-premise inference at the lowest TOPS/W. Co-processors that integrate with edge platforms enable real-time deep learning inference tasks with low power consumption and high cost-efficiency, supporting a wide range of neural networks, vision transformer models, and large language models (LLMs).
In conclusion, the collaboration between Hailo and Micron is a significant step towards addressing the challenges of edge AI. By offering power-efficient, cost-effective solutions, they are enabling a new era of AI applications that can run advanced models locally with low latency and power usage, preserving user privacy, reducing cloud dependency, and allowing deployment in environments with limited power or connectivity.
Technology in data-and-cloud-computing, such as LPDDR memory solutions by Micron and AI processors by Hailo, are playing crucial roles in edge AI applications. The combination of these technologies, with Hailo's AI processors providing efficient AI performance and Micron's LPDDR solutions ensuring fast and power-efficient data transfer, offers a cost-effective and scalable solution for sectors like automotive, industrial IoT, and mobile devices.
