12ad7a319086f4b888552dc4d2db6ad29ee78e5f
每个文件都是直接 cat 读完整 CCCL 源码后理解全部参数语义,
然后用大模型生成 BI-V100 适配版本。不使用 grep/sed/批量脚本。
segmented_sort.cuh (46→189 lines):
- 三层策略完整移植: large(RadixSort), medium(SubWarpMergeSort 16T), small(SubWarpMergeSort 2-8T)
- SM86 tuning: radix_bits=key>1?6:4, scale_reg_bound(256,23)
- BI-V100 SMEM cap for all three tiers
merge_sort.cuh (43→83 lines):
- SM50{256,11} SM52{512,15} SM60+{256,17} 三代参数
- nominal_4b_items_to_items scaling + unroll flag
merge.cuh (55→89 lines):
- SM52/SM60/SM80/SM90/SM100 五代参数
- bulk_copy=false (BI-V100 无 cp.async.bulk)
adjacent_difference.cuh (46→77 lines):
- nominal_8b_items_to_items(7) scaling
- may_alias → LOAD_CA vs LOAD_LDG
batch_memcpy.cuh (86→95 lines):
- small{128T,4buf,8B} + large{256T,32B} 双策略
- prefer_pow2_bits=false (SM70+)
find.cuh (32→39 lines):
- scale_mem_bound(128,16) + vec_size=4
find_bound_sorted_values.cuh (33→47 lines):
- SM80+: {512, N4B(15)} / SM60+: {256} / SM50: LOAD_LDG
project_6
Description
Languages
C++
41.8%
Cuda
31.6%
Python
22.2%
C
2.1%
CMake
1.1%
Other
1.1%