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projects/neosphere/ml-server/20250708-qwerty-summary.md

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+### **Comprehensive Project Plan: AI Server for Boltz with H100/L40 GPUs & Qumulo Storage**  
+
+---
+
+#### **1. Hardware & Infrastructure**  
+- **Server**: HP DL3XX Gen11 (512 GB RAM, 25 Gbit NICs, dual GPU slots).  
+- **GPUs**:  
+  - **Option 1**: 2x H100 (96 GB vRAM each, NVLink for inter-GPU communication).  
+  - **Option 2**: 2x L40 (46 GB vRAM each, PCIe 4.0 for inter-GPU communication).  
+- **Storage**: Qumulo cluster (300 TB) mounted via NFS on each compute node.  
+- **Networking**:  
+  - 25 Gbit bonding (active-backup mode) for redundancy and high throughput.  
+  - 25 Gbit transceivers (SFP+/QSFP+) for NICs and switches.  
+- **Power/Cooling**: Ensure PSU supports dual GPU power draw (e.g., H100: ~300W each, L40: ~250W each).  
+
+---
+
+#### **2. OS & Software Stack**  
+- **OS**: Ubuntu 24.04 LTS (latest stable release for H100/L40 support).  
+- **Automation**:  
+  - Use **Ansible** for OS installation, GPU driver setup, and cluster management (3 nodes).  
+  - Create playbooks for:  
+    - Ubuntu 24.04 installation.  
+    - NVIDIA driver + CUDA toolkit.  
+    - 25 Gbit NIC bonding.  
+    - NFS mount configuration for Qumulo.  
+- **CUDA/ROCm**: Install latest CUDA toolkit for NVIDIA GPUs (or ROCm for AMD).  
+
+---
+
+#### **3. Network Configuration**  
+- **Firewall**: Deploy **OPNsense** to:  
+  - Enforce Qumulo/NFS access controls.  
+  - Monitor traffic between compute nodes and storage.  
+- **Bonding**: Configure 25 Gbit NICs with `bonding-mode=active-backup` for failover.  
+- **NFS**: Optimize Qumulo NFS mounts with `noatime`, `async`, and `tcp` for large datasets.  
+
+---
+
+#### **4. GPU & Multi-GPU Setup**  
+- **Driver Installation**:  
+  - Install NVIDIA drivers (e.g., `nvidia-driver-535`) and verify `nvidia-smi`.  
+- **Multi-GPU Support**:  
+  - For H100: Enable **NVLink** for low-latency inter-GPU communication.  
+  - For L40: Use PCIe 4.0 for maximum bandwidth.  
+- **Boltz Compatibility**: Ensure Boltz is configured for multi-GPU use (CUDA-aware MPI or distributed memory).  
+
+---
+
+#### **5. Storage & Performance**  
+- **RAM**: 512 GB is sufficient for most workloads; monitor with `htop` or `free -h`.  
+- **Disk I/O**: Use NVMe SSDs for `/tmp` and `/var` to reduce latency.  
+- **Monitoring**:  
+  - Track GPU utilization (`nvidia-smi`), network throughput (`iftop`), and storage I/O (`iostat`).  
+  - Deploy **Prometheus + Grafana** for centralized metrics.  
+
+---
+
+#### **6. Security & Monitoring**  
+- **Security**:  
+  - Enable **SELinux/AppArmor** for access control.  
+  - Regularly back up configurations and critical data.  
+- **Logging**: Set up ELK stack for centralized logging.  
+- **Disaster Recovery**: Define steps for GPU/NIC failure, including hot-swappable components.  
+
+---
+
+#### **7. Additional Tasks**  
+- **Documentation**: Record all configurations (Ansible playbooks, firewall rules, GPU settings).  
+- **Testing**: Validate NFS performance and GPU utilization with sample datasets.  
+- **Optimization**: Tune Boltz for memory efficiency and parallel processing.  
+
+---
+
+### **Summary**  
+This project integrates high-performance hardware (H100/L40 GPUs, 25 Gbit networking) with Qumulo storage to run Boltz efficiently. Key steps include Ubuntu 24.04 setup, Ansible automation, GPU driver installation, NFS optimization, and security monitoring. Prioritize multi-GPU communication, RAM management, and disaster recovery to ensure reliability for large-scale data analysis.