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Awesome GitHub RepositoriesThroughput Optimizations

Techniques specifically targeting the increase of inference throughput using attention kernels and batching.

Distinct from Inference Performance Optimizers: Focuses on throughput-increasing mechanisms like paged KV caching and in-flight batching, rather than general compression/quantization.

Explore 2 awesome GitHub repositories matching artificial intelligence & ml · Throughput Optimizations. Refine with filters or upvote what's useful.

Awesome Throughput Optimizations GitHub Repositories

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  • dusty-nv/jetson-inferenceالصورة الرمزية لـ dusty-nv

    dusty-nv/jetson-inference

    8,734عرض على GitHub↗

    jetson-inference is a set of libraries and tools for executing optimized deep learning models on embedded GPU hardware. Its primary purpose is to enable real-time computer vision and AI inference at the edge with low latency and high throughput. The project distinguishes itself through high-performance streaming analytics and the ability to execute concurrent AI pipelines on auto-grade silicon. It provides specialized support for multi-sensor stream processing, utilizing zero-copy data transport to load camera frames directly into GPU memory. The codebase covers a broad surface of capabiliti

    Increases inference throughput using custom attention kernels, in-flight batching, and paged KV caching.

    C++caffecomputer-visiondeep-learning
    عرض على GitHub↗8,734
  • rlinf/rlinfالصورة الرمزية لـ RLinf

    RLinf/RLinf

    2,502عرض على GitHub↗

    RLinf is a distributed reinforcement learning orchestrator and embodied AI training framework. It provides the infrastructure to train vision-language-action models and robotic policies using a combination of reinforcement learning and supervised fine-tuning. The system is designed for scaling workloads across GPU clusters, managing the placement of actors, rollout workers, and environment components. It features a specialized robotics data collection pipeline for gathering teleoperated demonstrations and simulation trajectories into standardized replay buffers, alongside a hardware interface

    Maximizes simulator throughput by overlapping model forward passes with environment stepping across vectorized slices.

    Pythonagentic-aiembodied-aireinforcement-learning
    عرض على GitHub↗2,502
  1. Home
  2. Artificial Intelligence & ML
  3. Computer Vision Systems
  4. Computer Vision
  5. Object Detection and Tracking
  6. Edge Object Detection
  7. Inference Performance Optimizers
  8. Throughput Optimizations

استكشف الوسوم الفرعية

  • Rollout1 وسم فرعيTechniques for increasing the speed and volume of model sample generation during reinforcement learning rollouts. **Distinct from Throughput Optimizations:** Specifically targets the rollout phase of RLHF, distinct from general CV object detection throughput.