AIME MLC
The Deep Learning Framework Management System
The AIME Machine Learning Container Manager (AIME MLC) is a framework designed to streamline the deployment and management of deep learning environments based on Docker. The necessary libraries, GPU drivers, operating system libraries for various Deep Learning framework versions are bundled in preconfigured Docker containers and can be instantiated with just a single command. It emphasizes flexibility with significant benefits for researchers and engineers for experimenting with different AI models.
AIME MLC simplifies working with deep learning frameworks, such as TensorFlow and PyTorch, making it versatile for various applications in artificial intelligence. Users can customize environments with specific configurations, including versions of CUDA, drivers, OS and Python libraries, enabling users to define configurations tailored to specific projects and hardware setup s for fast switching between different projects or users.
AIME ML Container Manager
for Model Training & Inference
AIME MLC is particularly useful for AI research and development, enterprise AI solutions, and any application involving computationally intensive GPU usage like AI model training.
A key aspect of AIME MLC is its seamless integration into high performance GPU environments, such as those provided by AIME’s cloud infrastructure. This makes it particularly effective for applications requiring intensive computational resources, like training deep learning models on multi-GPU systems. The framework facilitates efficient resource allocation and management, allowing for optimized performance and scalability.
AIME servers and workstations ship with the AIME ML Container Manager preinstalled. Also integrated with AIME's high performance GPU cloud services, it provides a robust infrastructure to easily setup, accelerate, and navigate between deep learning AI projects and frameworks.
The AIME ML Container Manager makes life easier for developers so they do not have to worry about framework version installation issues.
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Step 1: Configure
Login through ssh or remote desktop to your dedicated instance. Everything is already installed and thanks to the AIME ML container system, your preferred deep learning framework can be configured right away with a single command:
> mlc create my-container Pytorch 2.5.0
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Step 2: Start working!
Your deep learning framework is ready to be used. You can now start developing, training or deploy your model, f.e. as an AIME API worker to scale up your application!
> mlc open my-container
AIME Benchmarking Suite
Measure Performance with Comprehensive Benchmarking Tools
As both a hardware and software company, AIME has developed a suite of benchmarking tools to evaluate and optimize AI performance across various hardware and software configurations.
The AIME Benchmark Suite provides detailed insights by:
- Benchmarking GPUs, from RTX 3090 to the latest H200 models.
- Evaluating AI model inference and training on diverse configurations and GPUs using popular open-source AI models.
- Benchmarking PyTorch and TensorFlow on multi-GPU setups, fully compatible with both NVIDIA CUDA and AMD ROCm environments.
Additionally, we offer a benchmarking tool for the AIME API Server, designed to test, monitor, and compare the performance of connected AI models (GPU workers). This enables performance evaluations to fine-tune AI deployments for maximum efficiency and reliability, enabling us to gain valuable insights, empowering our customers to make informed decisions about their hardware and software setups and ensuring optimal performance for their AI workloads.
Read our benchmarking results in our hands-on blog articles which we regularly publish on current open source AI models, for example:
- Pytorch Benchmarks
- GPU Benchmarks
- Llama 3.x Blog Articles
- FLUX-Benchmarks
Integrated in OpenWebUI, vLLM-ready
Data Sovereignty & Privacy with OpenWebUI & vLLM Integration
In response to the growing demand for data privacy and GDPR-compliant large language model integrations, AI agents, and RAG-solutions, AIME has extended the OpenWebUI framework with an AIME API compatible interface.
Use OpenWebUI as modern LLM chat frontend powered by the AIME API Server as scalable backend This allows you to run your own private version of a ChatGPT-like LLM, ensuring complete data sovereignty without compromising on performance or functionality.
Now you can operate large language models securely and in compliance with the highest data protection standards, all while maintaining full control over your data, choosing from the large pool of language models that vLLM supports. Run OpenWebUI on your own hardware as on-premise solution or connect to our GDPR compliant GPU cloud offerings.
Contact us
Call us or send us an email if you have any questions. We would be glad to assist you to find the best suitable compute solution.
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AIME GmbH
Marienburger Str. 1
10405 Berlin
Germany
