Ensuring Next Generation AI Network Performance with Precision Testing
Validate And Optimise Your Network For Next Generation AI Networking
As AI transforms industries, data center networks are being pushed to their limits. A new approach to network design and testing is necessary to ensure reliable performance. Learn how the industry's first AI workload traffic emulator validates new Ethernet infrastructure for next-gen AI applications.
Artificial intelligence (AI) systems are revolutionising digital industries in new and explorative ways. Understanding AI’s potential impact on data center networking, telecoms and enterprise digital transformation efforts is paramount. Testing actionable insights to better align your business with the AI revolution is a key to ensuring performance and reducing down time.
Testing AI data center infrastructure confirms high-speed Ethernet's ability to support the performance demands of at-scale AI workloads
AI Workload Emulation
Ensure AI networks are ready to meet emerging challenges. By emulating real-world workloads and identifying bottlenecks before deployment, data center operators can prepare to reap the full potential of AI infrastructure.
AI Growth
Gartner estimates spending on AI software will grow to $297.9B with a CAGR of 19.1% by 2027. While Generative AI (GenAI) software spend will rise from 8% of AI software in 2023 to 35% by 2027.
GPU Lab Requirements
AI workload emulation tools let operators simulate network conditions without needing to build costly GPU labs. These tools mimic real-world traffic and use protocols like RoCEv2 to optimize networks for training and inference workloads.
Test a wide range of network technologies, including Ethernet, IP, wireless, and optical networks.
Advanced analysis and reporting
Gain deep insights into network performance with powerful analytics and reporting tools.
Automated testing
Automate repetitive test tasks to improve efficiency and reduce testing time.
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