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Georgia Institute of Technology
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ASTRA-sim 3.0 reveals that high-fidelity simulations can significantly optimize distributed ML algorithms and infrastructure design.
Flint enables unprecedented flexibility in exploring distributed ML design spaces by leveraging compiler insights, allowing for workload representation across any cluster size.
StableHLO unlocks cross-architecture performance prediction for distributed ML, revealing accuracy trade-offs and simulator limitations without needing access to expensive, scaled-out hardware.
