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Ampere AI Efficiency: Computer Vision

Efficient AI Computer Vision (CV) Workloads

Energy Demand of Computer Vision (CV) Workloads

CV workloads place significant demands on energy consumption due to the computational complexity involved in processing visual data. CV tasks such as object detection, image recognition, and video analysis require extensive processing power to analyze and interpret images or videos.

Efficiently managing the energy demands of CV workloads is crucial for optimizing performance, reducing operational costs, and minimizing environmental impact. It requires a combination hardware optimizations and system-level optimizations to ensure optimal energy efficiency without compromising performance.

Key Benefits of Ampere Cloud Native Processors for Handling CV Workloads

Industry-Leading Performance

Ampere processors, built on a cloud native architecture, offer unmatched performance when compared to competing Intel and AMD processors based on the legacy x86 architecture. The advanced design and streamlined architecture of Ampere processors unlock exceptional processing power, enabling enterprises to meet the demands of compute-intensive computer vision workloads.

With higher core counts, increased cache sizes, and improved instruction sets, Ampere processors deliver faster and more efficient image and video processing, resulting in quicker insights and more accurate results.

Power Efficiency

Ampere processors prioritize power efficiency without compromising performance, making them an ideal choice for energy-conscious data centers and cloud environments, which is of particularly high importance due to growing electricity bills, estate costs, and water shortages in certain regions such as the Phoenix area.

With lower power consumption per compute unit, Ampere processors provide better energy efficiency compared to traditional x86 processors. This translates to reduced operational costs and environmental impact while maintaining high-performance capabilities for demanding computer vision workloads.

Scalability and Flexibility

Cloud Native Processors offer scalability and flexibility, allowing enterprises to efficiently handle varying workloads and accommodate increasingly demanding applications with growing data volumes and processing needs. They can scale horizontally by leveraging cloud infrastructure, enabling the processing of large-scale datasets and supporting multiple concurrent CV tasks.

Performance at the Rack Level and Performance per Watt - Competitive Comparison

Background on the Benchmarked CV Model: ResNet-50 v1.5

ResNet-50 v1.5 is a state-of-the-art convolutional neural network (CNN) model that has garnered significant attention in the field of artificial intelligence (AI), specifically in image classification tasks. Designed for accuracy, efficiency, and scalability, ResNet-50 v1.5 is a powerful tool for enterprises seeking to harness the potential of AI in their applications.

Comparative Results

On the measure of performance/rack Ampere Cloud Native Processors provide up to 266% better performance for running computer vision workloads compared to the legacy x86 architecture data center processors offered by AMD and Intel.

Performance/Rack 1S(ResNet-50 Throughput)

Ampere Cloud Native Processors redefine the boundaries of performance, scalability, and energy efficiency for AI workloads. With their cutting-edge architecture, seamless scalability, and advanced power management, Ampere processors empower enterprises to drive innovation, accelerate data processing, and achieve exceptional results in today's fast-paced digital landscape. Experience the next level of performance with Ampere Cloud Native Processors and unlock the true potential of your AI infrastructure.

CV: Industry Verticals Use Cases

Automotive and Transportation

A key component in autonomous vehicles, driver assistance systems, and traffic monitoring. It enables object detection, lane detection, pedestrian detection, and traffic flow analysis, leading to improved safety and efficiency on the roads.


Plays a crucial role in quality control, product inspection, and process optimization in manufacturing industries. It can identify defects, measure dimensions, and monitor production lines for efficiency and accuracy.


Utilized in medical imaging, disease diagnosis, and surgical assistance. It helps in analyzing medical scans, detecting anomalies, assisting in surgical procedures, and monitoring patient conditions.

Entertainment and Media

Enables augmented reality (AR), virtual reality (VR), and gesture recognition in gaming and interactive experiences. It enhances visual effects, facial animation, and object tracking in movies and digital media.


Used in retail for inventory management, shelf monitoring, and customer analytics. It can track stock levels, identify out-of-stock items, analyze shopper behavior, and enable cashier-less checkout experiences.

Future-proof your Enterprise and Innovate with Ampere Cloud Native Processors

Ampere Cloud Native Processors revolutionize data center infrastructure, setting a new standard for performance and efficiency in the era of technologies such as AI, machine learning, and edge computing. Ampere processors excel at energy efficiency, addressing the critical challenge of reducing data center power consumption.

By adopting Ampere processors, enterprises not only establish themselves as industry leaders in innovation but also contribute to a more sustainable infrastructure. This ensures they are well-prepared to navigate evolving industry trends and drive successful digital transformations with a clear focus on performance, efficiency, and curbing energy expenditures.

For more information on Ampere Solutions for AI

Visit, to learn about Ampere offering for AI. Download the Ampere Optimized AI Frameworks directly from the website free of charge or find out about our alternative AI software distribution channels. Benefit from 2-5 x additional raw performance provided by Ampere Optimized AI Frameworks (already included in the comparative presented benchmarks). You can reach the Ampere AI team directly at for any inquiries on running your specific recommender engine workloads.


All data and information contained herein is for informational purposes only and Ampere reserves the right to change it without notice. This document may contain technical inaccuracies, omissions and typographical errors, and Ampere is under no obligation to update or correct this information. Ampere makes no representations or warranties of any kind, including but not limited to express or implied guarantees of noninfringement, merchantability, or fitness for a particular purpose, and assumes no liability of any kind. All information is provided “AS IS.” This document is not an offer or a binding commitment by Ampere. Use of the products contemplated herein requires the subsequent negotiation and execution of a definitive agreement or is subject to Ampere’s Terms and Conditions for the Sale of Goods.

System configurations, components, software versions, and testing environments that differ from those used in Ampere’s tests may result in different measurements than those obtained by Ampere.

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Created At : August 16th 2023, 8:55:46 am
Last Updated At : February 14th 2024, 5:52:00 pm
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