pytorch - 💡(How to fix) Fix `torch.linalg._powsum` is slow on CPU for ord != 2 [1 participants]

"""Minimal benchmark: torch.linalg._powsum CPU regression for ord != 2.

For ord=2 the op is much faster than eager. For ord=3 (and other non-2 ords)
the CPU path is many times slower than the eager fallback x.abs().pow(p).sum().
"""

import time
import torch

def bench(fn, iters=500, warmup=20):
    for _ in range(warmup):
        fn()
    t0 = time.perf_counter()
    for _ in range(iters):
        fn()
    return (time.perf_counter() - t0) / iters * 1e6  # us

print(f"torch {torch.__version__}   CPU")
print(f"{'n':>8}  {'ord':>4}  {'powsum':>10}  {'eager':>10}  {'powsum/eager':>14}")
for n in (4_096, 65_536, 1_048_576):
    x = torch.randn(n)
    for p in (2.0, 3.0):
        t_ps    = bench(lambda: torch.linalg._powsum(x, p))
        t_eager = bench(lambda: x.abs().pow(p).sum())
        tag = "SLOW" if t_ps > t_eager * 1.5 else "ok"
        print(f"{n:>8}  {p:>4}  {t_ps:>9.1f}us  {t_eager:>9.1f}us  {t_ps/t_eager:>12.2f}x  {tag}")

---

torch 2.11.0   CPU                                                                                                                         
         n   ord      powsum       eager    powsum/eager                                                                                     
      4096   2.0        2.3us        5.5us          0.42x  ok
      4096   3.0       24.3us        5.6us          4.34x  SLOW                                                                              
     65536   2.0        7.7us      191.5us          0.04x  ok                                                                                
     65536   3.0      710.7us      143.1us          4.97x  SLOW
   1048576   2.0      144.6us     2485.5us          0.06x  ok                                                                                
   1048576   3.0     2505.8us     2742.2us          0.91x  ok

---

PyTorch version: 2.11.0
Is debug build: False
CUDA used to build PyTorch: 13.2
ROCM used to build PyTorch: N/A

OS: Ubuntu 24.04.4 LTS (x86_64)
GCC version: (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
Clang version: Could not collect
CMake version: version 4.3.0
Libc version: glibc-2.39

Python version: 3.12.3 (main, Mar  3 2026, 12:15:18) [GCC 13.3.0] (64-bit runtime)
Python platform: Linux-6.8.12-680-6063-coreweave-amd64-f81899c8-x86_64-with-glibc2.39
Is CUDA available: True
CUDA runtime version: 13.2.51
CUDA_MODULE_LOADING set to: 
GPU models and configuration: GPU 0: NVIDIA H100 80GB HBM3
Nvidia driver version: 580.126.20
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.9.20.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv.so.9.20.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn.so.9.20.0
/usr/lib/x86_64-linux-gnu/libcudnn_engines_precompiled.so.9.20.0
/usr/lib/x86_64-linux-gnu/libcudnn_engines_runtime_compiled.so.9.20.0
/usr/lib/x86_64-linux-gnu/libcudnn_graph.so.9.20.0
/usr/lib/x86_64-linux-gnu/libcudnn_heuristic.so.9.20.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops.so.9.20.0
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture:                         x86_64
CPU op-mode(s):                       32-bit, 64-bit
Address sizes:                        46 bits physical, 57 bits virtual
Byte Order:                           Little Endian
CPU(s):                               128
On-line CPU(s) list:                  0-127
Vendor ID:                            GenuineIntel
Model name:                           Intel(R) Xeon(R) Platinum 8462Y+
CPU family:                           6
Model:                                143
Thread(s) per core:                   2
Core(s) per socket:                   32
Socket(s):                            2
Stepping:                             8
CPU(s) scaling MHz:                   94%
CPU max MHz:                          4100.0000
CPU min MHz:                          800.0000
BogoMIPS:                             5600.00
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cat_l2 cdp_l3 cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect user_shstk avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hfi vnmi avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr ibt amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities
Virtualization:                       VT-x
L1d cache:                            3 MiB (64 instances)
L1i cache:                            2 MiB (64 instances)
L2 cache:                             128 MiB (64 instances)
L3 cache:                             120 MiB (2 instances)
NUMA node(s):                         2
NUMA node0 CPU(s):                    0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30,32,34,36,38,40,42,44,46,48,50,52,54,56,58,60,62,64,66,68,70,72,74,76,78,80,82,84,86,88,90,92,94,96,98,100,102,104,106,108,110,112,114,116,118,120,122,124,126
NUMA node1 CPU(s):                    1,3,5,7,9,11,13,15,17,19,21,23,25,27,29,31,33,35,37,39,41,43,45,47,49,51,53,55,57,59,61,63,65,67,69,71,73,75,77,79,81,83,85,87,89,91,93,95,97,99,101,103,105,107,109,111,113,115,117,119,121,123,125,127
Vulnerability Gather data sampling:   Not affected
Vulnerability Itlb multihit:          Not affected
Vulnerability L1tf:                   Not affected
Vulnerability Mds:                    Not affected
Vulnerability Meltdown:               Not affected
Vulnerability Mmio stale data:        Not affected
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Not affected
Vulnerability Spec rstack overflow:   Not affected
Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:             Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

Versions of relevant libraries:
[pip3] clip-anytorch==2.6.0
[pip3] dctorch==0.1.2
[pip3] DISTS_pytorch==0.1
[pip3] lovely-numpy==0.2.22
[pip3] mypy_extensions==1.1.0
[pip3] numpy==1.26.4
[pip3] onnx==1.20.1
[pip3] onnx-ir==0.2.0
[pip3] onnxscript==0.6.2
[pip3] torch==2.11.0
[pip3] torch_c_dlpack_ext==0.1.5
[pip3] torchaudio==2.11.0
[pip3] torchdata==0.11.0
[pip3] torchdiffeq==0.2.5
[pip3] torchsde==0.2.6
[pip3] torchtitan==0.1.0
[pip3] torchvision==0.26.0
[pip3] triton==3.6.0+git9844da95
[pip3] welford-torch==0.2.5
[conda] Could not collect