Hi all, hugetlb init parallelization has now been updated to v5. This version is tested on next-20240125. Update Summary: - Use prep_and_add_allocated_folios in 2M hugetlb parallelization - Update huge_boot_pages in arch/powerpc/mm/hugetlbpage.c - Revise struct padata_mt_job comment - Add 'max_threads' section in cover letter - Collect more Reviewed-by # Introduction Hugetlb initialization during boot takes up a considerable amount of time. For instance, on a 2TB system, initializing 1,800 1GB huge pages takes 1-2 seconds out of 10 seconds. Initializing 11,776 1GB pages on a 12TB Intel host takes more than 1 minute[1]. This is a noteworthy figure. Inspired by [2] and [3], hugetlb initialization can also be accelerated through parallelization. Kernel already has infrastructure like padata_do_multithreaded, this patch uses it to achieve effective results by minimal modifications. [1] https://lore.kernel.org/all/783f8bac-55b8-5b95-eb6a-11a583675000@xxxxxxxxxx/ [2] https://lore.kernel.org/all/20200527173608.2885243-1-daniel.m.jordan@xxxxxxxxxx/ [3] https://lore.kernel.org/all/20230906112605.2286994-1-usama.arif@xxxxxxxxxxxxx/ [4] https://lore.kernel.org/all/76becfc1-e609-e3e8-2966-4053143170b6@xxxxxxxxxx/ # max_threads This patch use `padata_do_multithreaded` like this: ``` job.max_threads = num_node_state(N_MEMORY) * multiplier; padata_do_multithreaded(&job); ``` To fully utilize the CPU, the number of parallel threads needs to be carefully considered. `max_threads = num_node_state(N_MEMORY)` does not fully utilize the CPU, so we need to multiply it by a multiplier. Tests below indicate that a multiplier of 2 significantly improves performance, and although larger values also provide improvements, the gains are marginal. multiplier 1 2 3 4 5 ------------ ------- ------- ------- ------- ------- 256G 2node 358ms 215ms 157ms 134ms 126ms 2T 4node 979ms 679ms 543ms 489ms 481ms 50G 2node 71ms 44ms 37ms 30ms 31ms Therefore, choosing 2 as the multiplier strikes a good balance between enhancing parallel processing capabilities and maintaining efficient resource management. # Test result test case no patch(ms) patched(ms) saved ------------------- -------------- ------------- -------- 256c2T(4 node) 1G 4745 2024 57.34% 128c1T(2 node) 1G 3358 1712 49.02% 12T 1G 77000 18300 76.23% 256c2T(4 node) 2M 3336 1051 68.52% 128c1T(2 node) 2M 1943 716 63.15% # Change log Changes in v5: - Use prep_and_add_allocated_folios in 2M hugetlb parallelization - Update huge_boot_pages in arch/powerpc/mm/hugetlbpage.c - Revise struct padata_mt_job comment - Add 'max_threads' section in cover letter - Collect more Reviewed-by Changes in v4: - https://lore.kernel.org/r/20240118123911.88833-1-gang.li@xxxxxxxxx - Make padata_do_multithreaded dispatch all jobs with a global iterator - Revise commit message - Rename some functions - Collect Tested-by and Reviewed-by Changes in v3: - https://lore.kernel.org/all/20240102131249.76622-1-gang.li@xxxxxxxxx/ - Select CONFIG_PADATA as we use padata_do_multithreaded - Fix a race condition in h->next_nid_to_alloc - Fix local variable initialization issues - Remove RFC tag Changes in v2: - https://lore.kernel.org/all/20231208025240.4744-1-gang.li@xxxxxxxxx/ - Reduce complexity with `padata_do_multithreaded` - Support 1G hugetlb v1: - https://lore.kernel.org/all/20231123133036.68540-1-gang.li@xxxxxxxxx/ - parallelize 2M hugetlb initialization with workqueue Gang Li (7): hugetlb: code clean for hugetlb_hstate_alloc_pages hugetlb: split hugetlb_hstate_alloc_pages padata: dispatch works on different nodes hugetlb: pass *next_nid_to_alloc directly to for_each_node_mask_to_alloc hugetlb: have CONFIG_HUGETLBFS select CONFIG_PADATA hugetlb: parallelize 2M hugetlb allocation and initialization hugetlb: parallelize 1G hugetlb initialization arch/powerpc/mm/hugetlbpage.c | 2 +- fs/Kconfig | 1 + include/linux/hugetlb.h | 2 +- include/linux/padata.h | 2 + kernel/padata.c | 14 +- mm/hugetlb.c | 234 +++++++++++++++++++++++----------- mm/mm_init.c | 1 + 7 files changed, 175 insertions(+), 81 deletions(-) -- 2.20.1
