Arm Adds AI Tool to Optimize Workloads Using Runtime Data

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Arm has made available a Dynamic Insights tool that leverages artificial intelligence (AI) models to generate recommendations for optimizing software running on its processors using actual data collected at runtime. Alex Spinelli, senior vice president for AI and developer platforms at Arm, said the Dynamic Insights tool provides both human developers and AI agents with verified evidence that enables them to optimize application performance using insights surfaced by AI models that have been trained by software engineering experts from Arm. That approach ensures AI guidance is based on how the workload and hardware behave together, rather than relying on source code assumptions alone, he added. Available as a module with a suite of open source Arm Performix tools, the overall goal is to reduce the level of expertise that previously was required to optimize code at a time when IT infrastructure resources are becoming more expensive, said Spinelli. In general, the number of workloads that now run on Arm-based platforms continues to exponentially increase. Historically, optimizing the performance of any application required a deep understanding of the underlying processor architecture. However, as large language models (LLMs) understand code better, it’s now possible to surface optimization insights in a way that is much more accessible to the average developer, noted Spinelli. That’s critical because, as the volume of code being generated in the age of AI continues to increase, it’s no longer feasible for software engineers to manually optimize every line of code. The issue, …

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