Scaling On-Device GPU Inference for Large Generative Models
a year ago
- #Machine Learning
- #GPU Inference
- #Generative AI
- Advancements in generative AI have led to large machine learning models transforming domains like image processing, audio synthesis, and speech recognition.
- On-device inference is crucial for privacy and efficiency, with GPUs being the most widely available on-device ML accelerator.
- ML Drift is an optimized framework that extends GPU-accelerated inference engines, enabling on-device execution of generative AI workloads with 10 to 100x more parameters than existing models.
- ML Drift addresses cross-GPU API development challenges and ensures compatibility across mobile and desktop/laptop platforms.
- The framework achieves an order-of-magnitude performance improvement over existing open-source GPU inference engines.