The Californian technology company is introducing an unlimited GPU rental platform at a fixed price for deep and machine learning projects

Glendale, California. GPULab, a modern data science platform that provides standards-based, turnkey, GPU-enabled research and development environments, is proud to announce its revolutionary unlimited GPU Rental platform. The new venture is aimed at data researchers who use excessive GPU processing for research project purposes.

GPU rentals, which are typically billed by the minute or hour, are known to be expensive and can likely stop or slow down deep learning projects in the academic research field. With the introduction of GPULabs Unlimited Monthly plans, the company is determined to solve this problem and contribute to scientific advancement by making this technology more accessible.

“As a company, we are passionate about the services we offer and strive to help our customers achieve exceptional results every day,” said Jeff Masud of GPULab. “One of the biggest barriers to success for many of our customers was the high cost of hourly GPU billing offered by other deep learning providers. We always want to be at the forefront of innovation. So we decided to break through industry pricing and offer unlimited GPU processing for a daily, weekly, or monthly fee. We are confident that this will not only prove very popular in the deep learning community, but could also revolutionize the current pricing models that dominate the market. ”

GPULab is a turnkey JupyterLab notebook environment on a feature-rich Ubuntu Linux operating system. GPULab offers a dedicated one for data scientists and research teams Nvidia K80 GPU for a flat rate. In addition, GPULab offers a fully integrated NVIDIA GPU / CUDA API Linux environment with pre-installed and configured data science languages ​​and runtimes such as Python, Julia, R and Octave as well as the latest popular data science libraries and frameworks including PyTorch, TensorFlow, Keras, Scikit-Learn and dozens more.

“Our approach to collaboration and security in data science is relatively straightforward,” adds Masud. Security is managed in GPULab’s private cloud facilities, which we own and operate in secure data centers in Los Angeles, Las Vegas, Denver and DC. ”Modern hardware firewalls and VPN services protect GPULab’s internal networks from potential security breaches . GPULab follows industry best practices for operating system security and provides limited and logged employee access to sensitive data services with a PCI compliant billing system.

For more information about the company and the range of daily, weekly and monthly subscriptions, please visit the website at

About GPULab

GPULab is a turnkey JupyterLab notebook environment on a feature-rich Ubuntu 20.04 Linux operating system. Gulab provides data scientists and research teams with a dedicated Nvidia K80 GPU for a flat fee. In addition, GPULab offers Jupyter Notebooks (managed by JupyterLab) and the Git application on a standard Linux file system for managing the source code. With unlimited GPU power, deep learning providers can leverage the power of world-class GPU processing at a fixed and low cost.

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Company Name: Deasil works
Interlocutor: Karl Hirsch
E-mail: Send e-mail
Phone: 818 945 0821
Address:121 W Lexington Dr Suite V500
City: Glendale
Status: CA 91203
Country: United States

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