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recomm.md

To optimize parallel processing in Azure OpenAI for better performance, you can consider the following best practices:

  1. Batch processing: By batching similar requests together, you can take advantage of parallel processing capabilities and maximize the efficiency of Azure OpenAI Service. This approach not only improves performance but also helps minimize costs by reducing the number of individual API calls.
  2. Model selection: The choice of model can significantly impact latency. For use cases that require the lowest latency models with the fastest response times, it is recommended to use the latest models in the GPT-3.5 Turbo model series.
  3. Generation size and Max tokens: Reducing the number of tokens generated per request can help reduce the latency of each request. You can set the max_token parameter on each call as small as possible, include stop sequences to prevent generating extra content, and generate fewer responses by adjusting the best_of & n parameters.
  4. Streaming: Streaming can help improve performance by reducing the latency of each request. It allows you to receive the response as it is generated, rather than waiting for the entire response to be completed.
  5. Concurrency: Increasing the number of concurrent requests can help improve performance by taking advantage of parallel processing capabilities. However, it is important to monitor resource usage and adjust the number of concurrent requests accordingly to avoid exceeding resource limits.
  6. Resource optimization: Azure OpenAI Service provides features such as Azure Application Insights to help you monitor and optimize resource usage. By tracking end-to-end transactions, identifying slow-performing components, and analyzing dependencies, you can make informed decisions to optimize your Azure OpenAI Service and improve overall efficiency.

By implementing these best practices, you can optimize parallel processing in Azure OpenAI for better performance and cost efficiency.

Citations: [1] https://www.softwareone.com/en-ch/blog/articles/2023/10/19/azure-openai [2] https://wesoftyou.com/ai/introduction-to-azure-openai-service/ [3] https://www.linkedin.com/posts/eugenezozulya_right-size-your-ptu-deployment-and-save-big-activity-7162800214301458432-Cn4j [4] https://www.reddit.com/r/OpenAI/comments/167lpn8/comparing_openai_gpt4_and_azure_gpt4_performance/ [5] https://learn.microsoft.com/en-us/azure/ai-services/openai/how-to/latency

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