Isaac SIM Workstation Balanced Configuration (September 2025 Edition) | TEGAKARI, an information media for research and development

The customer enquired about a workstation for Isaac SIM, as it would enable simultaneous control of multiple robots and the reproduction of complex scenes. They also wanted a configuration suitable for research purposes, including sensor processing and algorithm development.

Based on the information you provided, we proposed the following configuration.

CPU	Intel Xeon W7-2575X 3.00GHz (up to 3.0GHz at TB4.8) 22C/44T
memory	Total 128GB DDR5 5600 REG ECC 32GB ×4
storage	1TB SSD M.2 NVMe Gen5
Video	NVIDIA GeForce RTX5080 16GB
network	on board (1GbE x1 /10GbE x1)
Housing + power supply	Mid-tower case 1500W 80PLUS PLATINUM
OS	Ubuntu 22.04

About CPU

The Intel Xeon W7-2575 processor emphasizes multi-threaded performance and stability, making it ideal for running multiple processes simultaneously and processing sensors.

GPU selection

Equipped with a GeForce RTX 5080, it supports complex scenes and simultaneous control of multiple robots in Isaac SIM. It is also suitable for development using CUDA and TensorRT.

Memory/Storage Configuration

128GB of memory allows for simultaneous sensor processing and large-scale scene construction, while a 1TB SSD ensures fast data access and ample storage space.

Tegara's custom-made PC production service not only caters to the initial use, but also supports system expansion in anticipation of future expansion of research scale.
We not only offer customization of hardware specifications, addition of peripheral devices, and configuration suggestions to meet various software requirements, but also accept consultations regarding the construction of an entire research environment.
Please feel free to contact us and we will provide the best solution to suit your needs.

Keyword

・What is NVIDIA Isaac Sim?
NVIDIA Isaac Sim is a highly accurate, physics-based simulation platform for robotics research and development. It integrates with ROS2, generates synthetic data for AI training, and includes sensor models such as LiDAR, RGB cameras, and IMUs, enabling robot behavior verification in environments close to the real world. It runs on NVIDIA Omniverse and supports complex environment construction and multi-robot simulation. It's ideal for research into autonomous movement, manipulation, SLAM, reinforcement learning, and more.