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[pull] master from ggml-org:master#1072

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pull[bot] merged 4 commits intoLongLeCE:masterfrom
ggml-org:master
Apr 13, 2026
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[pull] master from ggml-org:master#1072
pull[bot] merged 4 commits intoLongLeCE:masterfrom
ggml-org:master

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@pull pull Bot commented Apr 13, 2026

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ORippler and others added 4 commits April 13, 2026 11:14
* 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
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
* use integer dot product for quantized KV flash attention

* small improvements

* fix SHMEM_STAGING indexing

* add missing KV type quants

* fixes

* add supported quants to FA tests

* readd fast paths for <8bit quants

* fix mmq gate and shmem checks
@pull pull Bot locked and limited conversation to collaborators Apr 13, 2026
@pull pull Bot added the ⤵️ pull label Apr 13, 2026
@pull pull Bot merged commit 75f3bc9 into LongLeCE:master Apr 13, 2026
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4 participants