Cancer center's $300-400K GPU dilemma: RTX Pro 5000 pairs vs one 8-GPU box for AlphaFold
starkruzr · reddit · 2026-10-24
A director of scientific computing at a cancer center is soliciting advice on spending a $300-400K budget for AlphaFold 2 workloads. Constraints: high VRAM per job with diminishing returns past 50GB, compute-heavy but tiny data, and millions of small files making storage IOPS the real challenge (solvable with prolog/epilog scripts moving data to node-local storage). Current setup: 70 Dell R7525 nodes with 3rd-gen EPYC, 1TB RAM and one A30 each, Slurm, 2x25Gb networking (400GbE planned). Options: one or two 8x RTX Pro 5000 72GB Blackwell systems (option 1), or buying bare RTX Pro 5000 cards to spread across nodes or pair up for 144GB VRAM per node (option 2.2, his lean). He'd rather keep the aging R7525s until they die and spend future refresh money on networking, storage and true training-grade GPUs.
More from Infra
- Grok does the math: running Kimi K3.1 Pro "locally" takes 18-32 H100s and $0.5-2M in hardware — giffmana · 2026-10-24
- A ~€1600 local LLM rig: i7-14700KF + RX 9070XT hits 70-90 tokens/sec — Snoo-2768 · 2026-10-24
- Jensen Huang: Nvidia software licensing could add ~$20B/year at $2,000 per enterprise GPU — sudoraohacker · 2026-10-24
- The 'compute spread': H100 rental vs open-source LLM token prices show -0.46 correlation — AccBalanced · 2026-10-24
- Neocloud premium is a speed premium: why Microsoft pays CoreWeave despite 5% borrowing costs — AccBalanced · 2026-10-24
- On-demand GPU rental indices hit all-time highs as even A100 prices rebound — AccBalanced · 2026-10-24