ggml-org/llama.cpp b8776

on GitHub

CUDA: Limit DeviceSegmentedSort to immediate mode (#21718)

• CUDA: Limit DeviceSegmentedSort to immediate mode

DeviceSegmentedSort is currently not capturable in a cuda graph. Hence,
we have to go for the slower DeviceSegmentedRadixSort in that case.

Perf numbers on RTX Pro 6000 Blackwell Max-Q:
DeviceSegmentedRadixSort in graph mode (i.e. CUDA Graphs)

ARGSORT(type=f32,ne=[2048,512,1,1],order=1): 12291 runs - 105.94 us/run - 8192 kB/run - 73.75 GB/s
ARGSORT(type=f32,ne=[4096,512,1,1],order=1): 10245 runs - 115.08 us/run - 16384 kB/run - 135.77 GB/s
ARGSORT(type=f32,ne=[8192,512,1,1],order=1): 5125 runs - 221.22 us/run - 32768 kB/run - 141.26 GB/s
ARGSORT(type=f32,ne=[16384,512,1,1],order=1): 2565 runs - 430.98 us/run - 65536 kB/run - 145.02 GB/s
ARGSORT(type=f32,ne=[32768,512,1,1],order=1): 1028 runs - 1185.83 us/run - 131072 kB/run - 105.41 GB/s
ARGSORT(type=f32,ne=[65536,512,1,1],order=1): 387 runs - 2748.62 us/run - 262144 kB/run - 90.95 GB/s

DeviceSegmentedSort in immediate mode

ARGSORT(type=f32,ne=[2048,512,1,1],order=1): 16388 runs - 71.17 us/run - 8192 kB/run - 109.78 GB/s
ARGSORT(type=f32,ne=[4096,512,1,1],order=1): 12294 runs - 81.38 us/run - 16384 kB/run - 192.00 GB/s
ARGSORT(type=f32,ne=[8192,512,1,1],order=1): 5125 runs - 240.81 us/run - 32768 kB/run - 129.77 GB/s
ARGSORT(type=f32,ne=[16384,512,1,1],order=1): 2565 runs - 406.60 us/run - 65536 kB/run - 153.71 GB/s
ARGSORT(type=f32,ne=[32768,512,1,1],order=1): 1285 runs - 873.23 us/run - 131072 kB/run - 143.15 GB/s
ARGSORT(type=f32,ne=[65536,512,1,1],order=1): 516 runs - 2288.46 us/run - 262144 kB/run - 109.24 GB/s

• Add test case for dispatch to DeviceSegmentedRadixSort

We currently lack a way to force graph mode in CUDA, patch callback to
invoke ggml_backend_compare_graph_backend twice to enforce each test to
run in graph mode