Repository: pytorch
Issue: torch.cumsum() super slow on 2d input
Labels: module: performance,module: cuda,triaged

### 🐛 Describe the bug



```
from triton.testing import do_bench
import torch

size = 1*1024 * 1024 

def bench_sum(tensor):
    return tensor.sum(dim=0)

def bench_cumsum(tensor):
    return tensor.cumsum(dim=0)

for d in [1, 2, 4, 8, 16, 32]:
    tensor = torch.rand(size, d, device='cuda')
    for f in [bench_sum, bench_cumsum]:
        print(f'{f.__name__:20}', d, do_bench(lambda : f(tensor)))
        
```

result
```
bench_sum            1 0.03623927757143974
bench_cumsum         1 0.047182515263557434
bench_sum            2 0.05706418305635452
bench_cumsum         2 83.61100769042969
bench_sum            4 0.08446607738733292
bench_cumsum         4 137.3924102783203
bench_sum            8 0.1467968076467514
bench_cumsum         8 244.81004333496094
bench_sum            16 0.271222323179245
bench_cumsum         16 332.3590087890625
bench_sum            32 0.5210586190223694
bench_cumsum         32 337.9122314453125
```

env and notebook:

https://gist.github.com/idning/4d5ece1ba07eda60e3cece2da01c0b57


### Versions

Collecting environment information...
PyTorch version: 2.2.1+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.3 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: 14.0.0-1ubuntu1.1
CMake version: version 3.27.9
Libc version: glibc-2.35

Python version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)
Python platform: Linux-6.1.58+-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.2.140
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: Tesla T4
Nvidia driver version: 535.104.05
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.9.6
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, 48 bits virtual
Byte Order:                         Little Endian
CPU(s):                             2
On-line CPU(s) list:                0,1
Vendor ID:                          GenuineIntel
Model name:                         Intel(R) Xeon(R) CPU @ 2.20GHz
CPU family:                         6
Model:                              79
Thread(s) per core:                 2
Core(s) per socket:                 1
Socket(s):                          1
Stepping:                           0
BogoMIPS:                           4399.99
Flags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology nonstop_tsc cpuid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single ssbd ibrs ibpb stibp fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm rdseed adx smap xsaveopt arat md_clear arch_capabilities
Hypervisor vendor:                  KVM
Virtualization type:                full
L1d cache:                          32 KiB (1 instance)
L1i cache:                          32 KiB (1 instance)
L2 cache:                           256 KiB (1 instance)
L3 cache:                           55 MiB (1 instance)
NUMA node(s):                       1
NUMA node0 CPU(s):                  0,1
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit:        Not affected
Vulnerability L1tf:                 Mitigation; PTE Inversion
Vulnerability Mds:                  Vulnerable; SMT Host state unknown
Vulnerability Meltdown:             Vulnerable
Vulnerability Mmio stale data:      Vulnerable
Vulnerability Retbleed:             Vulnerable
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass:    Vulnerable
Vulnerability Spectre v1:           Vulnerable: __user pointer sanitization and usercopy barriers only; no swapgs barriers
Vulnerability Spectre v2:           Vulnerable, IBPB: disabled, STIBP: disabled, PBRSB-eIBRS: Not affected
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Vulnerable

Versions of relevant libraries:
[pip3] numpy==1.25.2
[pip3] torch==2.2.1+cu121
[pip3] torchaudio==2.2.1+cu121
[pip3] torchdata==0.7.1
[pip3] torchsummary==1.5.1
[pip3] torchtext==0.17.1
[pip3] torchvision==0.17.1+cu121
[pip3] triton==2.2.0
[conda] Could not collect

cc @ptrblck