llm theoretical performance analysis tools and support params, flops, memory and latency analysis.

Hands-on Machine Learning Infrastructure on Kubernetes. Using Microk8s/Ubuntu on Paperspace Cloud.

code for benchmarking GPU performance based on cublasSgemm and cublasHgemm

A systematic CPU/GPU performance study of lightgbm and xgboost classifiers for different data shapes and hardware setups.

Disable GPU Thermal and Change GPU Governor to performance. (Only for snapdragon devices).

This repository provides the latest benchmarks for the CHARMM/pyCHARMM program on GPUs

📊 Mobile VR Performance Optimization Project

Professional GPU Performance Testing Suite for dual GPU setup (AMD RX 6600 + NVIDIA RTX 3050) with comprehensive monitoring tools, crash-safe scripts, and thermal management optimized for ASRock X570 Taichi + Ryzen 7 5700X

Comprehensive machine learning benchmarking framework for AMD MI300X GPUs on Dell PowerEdge XE9680 hardware. Supports both inference (vLLM) and training workloads with containerized test suites, hardware monitoring, and analysis tools for performance, power efficiency, and scalability research across the complete ML pipeline.