KWAM on the NVIDIA H100 fleet
The orchestration layer that sits above your accelerators. It never touches the silicon's compute, only the resilience of the Python codebases and data that run on it.
An H100 fleet is the most concentrated, most valuable compute most teams will ever run. KWAM is the resilience and orchestration layer that sits above it. It erasure-codes your Python codebase and its data into signed, content-addressed fragments, then spreads them across the fleet's natural fault domains so the loss of any single domain stays recoverable instead of fatal.
From one GPU up to the whole fleet
KWAM reads the physical shape of your deployment and treats every level of it as an independent fault domain. The deeper your fleet, the more places it can lose at once and still rebuild.
On a Lenovo ThinkSystem SR680a V3, that hierarchy runs from the individual H100, to the SXM5 baseboard, to the node, to the rack and power domain, and out to the availability zone. The placer keeps fragments in distinct domains at every level, so a dead GPU, a failed board, or a lost node never holds the only copy of your code.
Fault-domain ladder
GPU
↳ SXM5 baseboard (×8)
↳ node (SR680a V3)
↳ rack & power domain
↳ availability zone
anti-affinity keeps fragments in distinct domains at every level
Built for the way H100 fleets actually fail
An 8-GPU SXM5 board gives KWAM eight independent placement domains in a single chassis. The anti-affinity placer keeps fragments in distinct domains, so a failed GPU or board never takes the only copy of your codebase.
Every fragment read from an H100 node is SHA-256 verified. Corruption from a flaky link, a thermal event, or a radiation upset is surfaced immediately, never returned as a silently-corrupted byte.
KWAM's model can re-rank where to place or heal fragments across the fleet, but the deterministic RS/LRC codecs produce every byte. The model never produces a data byte, and never mints consent to a node.
As nodes drop and return, the healer rebuilds missing fragments from the survivors without pausing your workload. Reconstruction is deterministic and content-verified at every step.
protect() and recover() wrap any Python codebase. No rewrite of your training or inference stack, and nothing about the H100 compute path changes.
Push past the code distance and data is gone. KWAM reports exactly what it could not recover, with the sample size and confidence behind every measured recovery rate. Knowing is not the same as recovering, and we never blur the two.
NVIDIA, H100, and SXM are trademarks of NVIDIA Corporation. ThinkSystem is a trademark of Lenovo. Hardware shown for illustration. KWAM is independent software and is not affiliated with or endorsed by NVIDIA or Lenovo.