Showing 9 of 9 projects
A high-throughput, memory-efficient inference and serving engine for large language models (LLMs).
A unified deep learning system for efficient large-scale model training and inference with advanced parallelism strategies.
An open-source inference serving platform for deploying AI models from multiple frameworks across cloud, data center, and edge devices.
A Python library for building production-ready model inference APIs, job queues, and multi-model serving systems for AI applications.
An LLM acceleration library for Intel XPU (GPU, NPU, CPU) to speed up local inference and finetuning of popular models.
A collection of best practices and guidelines for optimizing Vulkan applications on mobile devices with Arm GPUs.
A PyTorch implementation of TResNet, a high-performance convolutional neural network architecture optimized for GPU training and inference.
A GPU-optimized particle system ported from Alternativa3D to Starling Framework for mobile rendering.
Converts Flash MovieClips to Starling IAnimatable sprites while preserving display list hierarchy and optimizing GPU memory.
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