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A Python tool that extracts telemetry data from various space launch videos using computer vision and OCR. Analyzes flight parameters (speed, altitude, engine status), calculates derived metrics, and generates visualizations for comparing launch performance characteristics. Features parallel processing and a user-friendly command-line interface.
Implementation of Flash-DLM (paper: FlashDLM: Accelerating Diffusion Language Models via Efficient KV Caching and Guided Diffusion). Provides training-free methods to accelerate diffusion language model inference.
[ICML 2025] This is the official PyTorch implementation of "🎵 HarmoniCa: Harmonizing Training and Inference for Better Feature Caching in Diffusion Transformer Acceleration".
Accelerating LLM inference with techniques like speculative decoding, quantization, and kernel fusion, focusing on implementing state-of-the-art research papers.