Synthetic Biology AI Big Data CenterSynthetic Biology AI Big Data Center
Simplified Description of Synthetic Biology AI Big Data Center Equipment

1. Computing power cluster
40-112 core Xeon/EPYC server nodes x 10-50 units, with a single node of 512GB-1.5 TB of memory and an overall peak of 1-5 PFLOPS.
GPU acceleration: A100/H100 or RTX 6000 Ada, single card 80 GB HBM, supporting deep learning and molecular dynamics.

2. High speed storage
Tiered architecture: 15 TB NVMe cache+252 TB parallel flash array+10 PB cold storage tape library, read and write bandwidth of 100 GB/s.

3. Network
• Computing network: 100 Gb InfiniBand non blocking fat tree, latency<1 μ s;
Business network: 10 GbE redundant links;
• Management network: 1 GbE independent out of band channel.

4. Data Lake and Software
Hadoop/S3 compatible object storage with built-in version control;
Containerized scheduling (Kubernetes+Slurm), one click deployment of 200+bioinformatics processes such as AlphaFold, ColabFold, Cellpose, etc;
AI frameworks: PyTorch, TensorFlow, RAPIDS, supporting GPU distributed training.

5. Laboratory automation interface
High throughput microreactor array (milli upgrade) automatically feeds and samples, and real-time streams of DO, pH, and OD data into the center;
Robot arm+RFID sample tracking ensures a closed loop of "experiment data model".

6. Visualization and Security
4 × 4K large screen displays real-time pipeline status;
Zero trust gateway, full link encryption, compliant with GDPR/Level 3 security.

one-sentence summary
The center consists of three major components: "CPU+GPU supercomputing+100TB level parallel storage+100G network". The laboratory data is then fed in real-time through an automated experimental interface for AI model training and reverse guidance of experiments, forming a "data algorithm experiment" closed loop.