Slide 36
Slide 36 text
Performance Summary
§ Effective cost leadership in the cloud for AI workloads, Ability to scale up for AI workloads as needed
§ Overall performance against ANY workload with no ongoing tuning (Placement groups, number of FE’s)
§ Metadata/mixed IO/latency performance matters: It’s not just about throughput
§ Cloud Performance that can beat On-Prem
§ #1 in all SPEC categories, whether it's a raw number or effective#
• Futures
• STAC-M3, ML-Perf, STAC-ML, IO-500 and others
• Mix of cloud and on-prem benchmarking including WEKApod base config.
• Transparent, publicly documented and repeatable synthetic results (FIO, El Bencho, VDbench, etc.)
Confidential: Under Embargo Until March 14.