How does this skill help with cost-effective development?

By establishing baselines and encouraging 'narrow scope' testing (like running specific test modules instead of full suites), it reduces unnecessary compute cycles and cloud costs.

Does this skill support NVIDIA GPU monitoring?

Yes, it includes specific integration for NVIDIA tools like nvidia-smi, nsys, and nvprof to track GPU utilization and memory usage.

When is the best time to trigger this performance skill?

You should use it at the start of a session or before launching any task expected to pin hardware resources for more than one minute.

What does the cpu-gpu-performance skill do?

It provides a framework for Claude to monitor, profile, and optimize CPU and GPU usage during resource-intensive tasks like software builds or model training.

Can I use this for profiling C++ or Rust applications?

Absolutely. It supports various profiling tools including perf, Intel VTune, and cargo flamegraph for deep analysis of CPU-bound work.

CPU & GPU Performance Optimizer

Name: CPU & GPU Performance Optimizer
Author: Ven0m0

byVen0m0

분석 및 모니터링

Monitors and optimizes system resource consumption for intensive development, build processes, and machine learning tasks.

소개

The CPU & GPU Performance Optimizer is a specialized skill designed to manage and reduce resource overhead during computationally expensive operations. It guides developers through a structured discipline of establishing performance baselines, narrowing task scopes to avoid redundant work, and utilizing professional profiling tools. By enforcing workload throttling and sequencing, this skill prevents system starvation and ensures that resource-heavy commands—such as deep learning training or large-scale software compilation—stay within defined time and hardware budgets.

주요 기능

Automated resource baseline tracking using uptime, ps, and nvidia-smi
Integration with professional profiling tools like perf, flamegraphs, and nsys
0 GitHub stars
Workload throttling and sequencing to prevent hardware starvation
Selective testing and build scoping to minimize redundant computation
Detailed resource cost logging for better infrastructure cost management

사용 사례

Profiling application hot paths to identify bottlenecks before scaling production workloads
Monitoring GPU utilization and memory pressure during intensive machine learning model training
Optimizing large-scale CI/CD build pipelines to reduce execution time and resource costs

소개

주요 기능

Automated resource baseline tracking using uptime, ps, and nvidia-smi
Integration with professional profiling tools like perf, flamegraphs, and nsys
0 GitHub stars
Workload throttling and sequencing to prevent hardware starvation
Selective testing and build scoping to minimize redundant computation
Detailed resource cost logging for better infrastructure cost management

사용 사례

Profiling application hot paths to identify bottlenecks before scaling production workloads
Monitoring GPU utilization and memory pressure during intensive machine learning model training
Optimizing large-scale CI/CD build pipelines to reduce execution time and resource costs