Analyze GPU program performance via visualization and metric collection.
npx skills add https://github.com/dongg622/china-ai-chip-skill --skill mcprofiler
Please help me install this Agent Skill. Skill: mcprofiler Source: https://github.com/dongg622/china-ai-chip-skill/tree/main/MetaX/mcprofiler Command: npx skills add https://github.com/dongg622/china-ai-chip-skill --skill mcprofiler
This Skill provides GPU performance analysis tools that enable developers to understand and optimize their GPU-accelerated applications efficiently.
Launch mcProfiler on Windows, configure your task parameters, and run analysis with simple commands to visualize GPU performance metrics.
High-intent search queries and answers about installing and using this skill.
To visualize GPU performance metrics and find bottlenecks, you can use this Skill to collect detailed data and display RoofLine models alongside memory, computation, and scheduling indicators in a GUI for fine-tuning workloads.
A RoofLine model is a visual representation of hardware limits used during GPU performance tuning. This Skill visualizes it alongside scheduling metrics to help developers identify bottlenecks and assess hardware utilization.
You need Windows to run the GUI interface for GPU profiling, and you can configure SSH access to Linux systems to gather execution data remotely for your analysis.
The best way to collect GPU performance data during execution is using the libmcToolsExt library, which this Skill requires to gather detailed metrics for system diagnostics and hardware utilization assessment.
Yes, you can use this GPU performance analysis tool for system diagnostics and hardware utilization assessment, as it specifically gathers and visualizes metrics applicable to these tuning tasks.
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