A customer involved in bioinformatics research contacted us to discuss their idea of upgrading to a more high-performance configuration, as they were building and operating a virtual environment for the purposes of RNA-seq analysis, gene expression analysis, and microbial flora analysis, but felt that their current workstation had reached its limits in processing power.
The current workstation design is as follows:
CPU: Intel Xeon E-2124G
RAM: 16GB
Storage: 3.64TB
GPU: NVIDIA Quadro P400
Based on the information you provided, we proposed the following structure:
| CPU | Intel Xeon W7-2595X 2.80GHz (up to 3.0GHz at TB4.8) 26C/52T |
| memory | Total 256GB DDR5 5600 REG ECC 64GB x 4 |
| Storage 1 | 2TB SSD S-ATA (No RAID) |
| Storage 2 | 2TB SSD S-ATA (No RAID) |
| Storage 3 | 4TB SSD M.2 NVMe Gen4 |
| Video | NVIDIA RTX 4500 Ada 24GB (DisplayPort x 4) |
| network | on board (2.5GbE x 1 / 10GbE x 1) |
| Housing + power supply | Mid-tower chassis 1600W 80PLUS TITANIUM |
| OS | Microsoft Windows 11 Pro for WS 64bit |
| Other (1) | Dual boot setup on 2TB SSD |
| Other (2) | Ubuntu22.04 dual boot setup |
This is a high-performance machine for bioinformatics research that supports genome analysis and structure prediction and can operate multiple tools in a virtual environment.
Parts configuration that supports large-scale calculations
In research that involves performing multiple processes in parallel, such as RNA-seq analysis and bacterial flora analysis, the availability of a high-spec machine environment is crucial.Directly linked to analysis efficiencyTo do.
This configuration uses the 26-core, 52-thread Intel Xeon W7-2595X.
Stable performance even in large-scale calculationsIt is also suitable for complex operations that utilize Docker container technology.
In addition, by installing 256GB of DDR5 ECC memory,Reduce calculation delays.
Even if multiple virtual environments are launched at the same time, the speed does not decrease.Maintain a comfortable working environmentAvailable
For graphics, the computer uses the NVIDIA RTX 24 Ada with 4500GB of GPU memory.
Suitable for structure prediction tools such as AlphaFold3, and for medium-scale analysis.Stable processing through proper settingscan be done.
Assuming GUI operation in a Linux environment, the OS configuration was changed from WSL2 to a dual boot configuration.
These components enable stable and efficient operation of everything from parallel analysis to structure prediction using GPUs.
For those who are active in these fields
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This specification is a well-balanced design that can meet not only current applications but also new research needs.
We can flexibly accommodate customization based on your budget, the software you use, and future operational policies, so please feel free to contact us even if you have conditions other than those listed here.
Keyword・What is QIIME2? QIIME2 is an open source software package for microbiome analysis. ・What is AlphaFold3? AlphaFold3 is a program that uses deep learning to predict the three-dimensional structure of proteins and complexes.
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