TheStage AI Platform: Introduction

Introduction

TheStage AI: https://app.thestage.ai is an integrated platform tailored for AI researchers, including both individual professionals and organizations. It is primarily designed to address the challenges associated with deep neural network (DNN) inference acceleration.

TheStage AI provides a robust toolkit for the pruning, quantization, and compiling of DNN models for specific hardware, enabling researchers to develop and deploy efficient models on edge devices and GPUs.

Furthermore, TheStage AI introduces a new approach to organizing the Research & Development process. With the TheStage CLI, researchers can interact with cloud infrastructure as easily as running code on their local laptops, streamlining the workflow and enhancing productivity.

Currently, the platform is in its beta stage and is evolving to meet the needs of researchers. Despite being in beta, TheStage AI already offers the following key functionalities:

  • Access to the proprietary Qlip framework for optimizing inference

  • Computational cluster organization

  • Research and development process organization.

Qlip

The heart of TheStage AI is Qlip: a toolkit specifically designed to optimize and streamline quantization, pruning, and inference tasks for neural networks. Qlip enables the development and deployment of more efficient models that can run on resource-constrained devices such as mobile phones and embedded systems. By using Qlip, researchers can achieve significant improvements in model performance and resource efficiency.

The toolkit includes the following components:

  • Qlip.Train: Contains fine-tuning strategies for frequently used cases. It can be easily customized in terms of model, data, and fine-tuning time.

  • Qlip.Compress: SDK and a set of quantization and pruning algorithms synchronized with the existing hardware.

  • Qlip.Deploy: Provides model building and compilation APIs for a wide range of devices.

  • Qlip.Serve: SDK for deploying inference endpoints on the cloud.

Hardware and Organization Framework

Working with deep learning models requires robust hardware and effective organization of these resources. TheStage AI ensures that researchers have the necessary infrastructure to manage and utilize hardware efficiently.

Computational Resources Management

TheStage AI platform allows researchers to rent computational resources from cloud providers and connect existing self-hosted servers to the computational cluster on TheStage AI. This unified access point bridges the gap between researchers and major cloud providers, offering access to high-quality hardware and simplifying the process of renting and managing these resources.

Research and Development Process Organization

TheStage AI provides an infrastructure over the computational cluster designed for organizing, executing, and analyzing research and development processes. This setup ensures that researchers can efficiently share hardware resources, manage their research and development processes, and iterate on their work, leading to faster and more reliable outcomes.

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