Sunday, April 21, 2024

Improving AI Network Testing In Data Centers

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The platform accelerates AI/ML network design and validation, providing scalable testing solutions for data centres to enhance performance and efficiency.

Improving AI Network Testing In Data Centers
Improving AI Network Testing In Data Centers

Keysight Technologies, Inc. has entered the artificial intelligence (AI) and machine learning (ML) infrastructure ecosystem by launching the Keysight AI Data Center Test Platform. This platform is designed to speed up innovation in AI/ML network validation and optimization, offering improvements in benchmarking new AI infrastructures with scale and efficiency.

The use and deployment of AI are increasing across all industrial sectors, with the training and delivery of new AI models being a priority for companies. AI/ML workloads process volumes of data, necessitating networking bandwidth and computing performance to minimise training time. However, designing and validating large-scale “what-if” scenario assessments is expensive for even the largest AI operators.

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To address this challenge and expedite the design and testing of AI/ML infrastructure, the AI Data Center Test Platform provides AI workload emulation, benchmarking applications, and dataset analysis tools. These features enhance the performance of the AI/ML cluster network fabric.

To accelerate AI/ML network design, Keysight’s solution for data centres emulates high-scale AI workloads with measurable fidelity, offering deep insights into collective communication performance. It simplifies the benchmarking process by validating AI network fabric with pre-packaged benchmark applications built through partnerships with the largest AI operators and AI infrastructure vendors.

Additionally, the solution executes defined AI/ML behavioural models, enabling sharing between users and customers to help reproduce experiments. It offers a choice of test engines, allowing users to choose between AI workload emulation on Keysight hardware load appliances and software endpoints on real AI accelerators to compare benchmarking results.

The platform facilitates large-scale validation and experimentation with fabric design realistically and cost-effectively. This solution complements the testing of AI/ML workloads using GPUs, offering AI operators a more scalable, robust, and integrated AI testing platform.

Martin Hull, Vice President, Cloud and Platforms at Arista Networks said, “Keysight’s AI Test Platform is a valuable tool to validate Arista’s technological leadership in AI network design.”

Nidhi Agarwal
Nidhi Agarwal
Nidhi Agarwal is a journalist at EFY. She is an Electronics and Communication Engineer with over five years of academic experience. Her expertise lies in working with development boards and IoT cloud. She enjoys writing as it enables her to share her knowledge and insights related to electronics, with like-minded techies.


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