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PML 3.0.0 large-triplet timings

These measurements compare v3.0.0 with v2.9.0. For the current release, see the 3.0.1 performance overview and 3.0.1 timings and memory measurements.

3 fresh processes per configuration, each averaging 3 blocks of 10 forward/backward pairs after warmup. Times are milliseconds per pair; peak memory is total PyTorch allocation in MiB. Encoder, optimizer, and data loading are excluded. This campaign measures timing and memory; full-gradient agreement and capacity require separate evidence.

GPU GPU memory (GiB) Host CPU PyTorch CUDA
RTX 4090 23.52 AMD EPYC 7352 24-Core Processor 2.14.0+cu130 13.0
RTX 5090 31.36 AMD Ryzen 9 9950X 16-Core Processor 2.14.0+cu130 13.0
L40S 44.39 AMD EPYC 9354 32-Core Processor 2.14.0+cu130 13.0
A100-SXM4-80GB 79.25 AMD EPYC 7742 64-Core Processor 2.14.0+cu130 13.0
H100 80GB HBM3 79.18 Intel(R) Xeon(R) Platinum 8470 2.14.0+cu130 13.0

CSV measurements retain full precision and statuses.

standard: 128 dimensions, 4 samples per class for pair/triplet losses, 1,024 classes for proxy losses.

All-triplet · standard · float32 · batch 8,192

GPU Version Status Total Forward Backward Process range Peak MiB
RTX 4090 2.9.0 ok 3,041 2,448 593 3,027–3,058 16,528
RTX 4090 3.0.0 ok 289 91.6 198 289–289 15,950
RTX 5090 2.9.0 ok 838 619 219 837–840 16,566
RTX 5090 3.0.0 ok 194 54.6 139 194–194 15,989
L40S 2.9.0 ok 1,530 1,161 368 1,477–1,557 16,528
L40S 3.0.0 ok 375 126 249 375–375 15,950
A100-SXM4-80GB 2.9.0 ok 2,540 2,137 402 2,532–2,553 16,528
A100-SXM4-80GB 3.0.0 ok 293 54.9 238 293–293 15,950
H100 80GB HBM3 2.9.0 ok 1,316 1,110 206 1,273–1,392 16,566
H100 80GB HBM3 3.0.0 ok 158 32.4 126 158–158 15,989

Raw evidence

RTX 4090: raw records · configuration and hardware

RTX 5090: raw records · configuration and hardware

L40S: raw records · configuration and hardware

A100-SXM4-80GB: raw records · configuration and hardware

H100 80GB HBM3: raw records · configuration and hardware