Compute cost & hardware
Bind the declared workload to physical hardware evidence, measured for the run's own process - not the whole machine.
Compute-cost attestation
Declare a model card so K-Veritas knows the scale of the work:
print("KVERITAS_MODEL params=25600000 arch=resnet50 precision=fp16")
print("KVERITAS_WORKLOAD dataset_size=1281167 epochs=90 batch_size=256")At seal time a certificate checks the declared FLOPs against the hardware evidence using three physical bounds. A hard time or energy violation is a physical impossibility, so it is non-deniable - anyone can recompute the inequality from the inputs printed on the report.
Declared FLOPs cannot exceed device peak throughput times GPU-active seconds.
Declared FLOPs cannot exceed measured joules divided by the minimum energy per FLOP.
Declared model weights should fit within the observed GPU memory.
Verdicts are PASS, REVIEW, FABRICATION-IMPOSSIBLE, or N/A. It proves the work ran at the declared scale; it does not prove the result is correct.
Hardware consistency (HMCA)
The Hardware-Metric Consistency Analyzer runs at seal time and flags metrics that do not match observed hardware activity - a metric reported with no measurable computation, or GPU claims on a CPU-only machine. It produces a score and verdict, both in the report.
Per-process measurement
K-Veritas measures only the process tree that kveritas run launched - CPU time and memory from the process tree, GPU memory and utilization filtered to its PIDs, and GPU power scaled by its share of utilization. If a browser or another job is running at the same time, it does not inflate the run's numbers.
/proc and nvidia-smi). On macOS and Windows the sampler falls back to system-wide readings until per-process support lands there.