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domaingcore.com
summary**Summary:**

- **Goal:** To assess inference speed on NVIDIA's H100 GPU for genomic processing.
- **Methodology:** Used an NVIDIA-developed model without customization.
- **Collaboration Benefits:**
- Up to 50x faster variant calling tasks.
- Cost savings via on-demand GPUs, avoiding upfront hardware investments.
- Scalable infrastructure with dynamic resource allocation.
- Data sovereignty and security in a compliant cloud environment.
- **Processing Times (H100 GPUs):**
- Range from 13 minutes (haplotypecaller with 2 GPUs) to nearly 90 minutes (Deepvariant with 8 GPUs).
- GPU overhead can slow processing time when memory limits are reached.
- **Future Plans:**
- RTU HPC plans to expand AI applications beyond genomics using Cloud GPUs.
- Potential collaboration with Gcore for optimizing GPU configurations and exploring AI Inference opportunities.
- **Global Impact:** BMC's work contributes to the international 1 Million Genomes Project, making genomic information more accessible.
- **Benchmark Results (H100 GPUs):**
- fq2bam and haplotypecaller showed shortest processing times with consistent results across 2, 4, and 8 GPUs.
- **Future Vision:** Liepa sees the future of AI in healthcare as fast, flexible, and sovereign.
titleGcore | Global Hosting, CDN, Edge and Cloud Services
descriptionWe provide powerful solutions that will help your business grow globally. Try our superior performance for free
keywordscloud, performance, infrastructure, high, game, saber, streaming, platform, demand, edge, servers, more, scale, metal, team, network, time
upstreams
downstreams
nslookupA 5.188.126.61
created2025-04-12
updated2025-05-14
summarized2025-05-14

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