[Installation]: Feature 'f16 arithemetic and compare instructions' requires .target sm_53 or higher

[fxavier-maf]

Your current environment

The output of `python collect_env.py`

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: Amazon Linux 2 (x86_64) GCC version: (GCC) 9.2.0 Clang version: Could not collect CMake version: version 3.29.2 Libc version: glibc-2.26

Python version: 3.9.19 (main, Mar 21 2024, 17:11:28) [GCC 11.2.0] (64-bit runtime) Python platform: Linux-4.14.336-257.568.amzn2.x86_64-x86_64-with-glibc2.26 Is CUDA available: True CUDA runtime version: 11.4.152 CUDA_MODULE_LOADING set to: LAZY GPU models and configuration: GPU 0: Tesla M60 Nvidia driver version: 550.54.17 cuDNN version: Could not collect 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 Byte Order: Little Endian CPU(s): 16 On-line CPU(s) list: 0-15 Thread(s) per core: 2 Core(s) per socket: 8 Socket(s): 1 NUMA node(s): 1 Vendor ID: GenuineIntel CPU family: 6 Model: 79 Model name: Intel(R) Xeon(R) CPU E5-2686 v4 @ 2.30GHz Stepping: 1 CPU MHz: 2700.019 CPU max MHz: 3000.0000 CPU min MHz: 1200.0000 BogoMIPS: 4600.02 Hypervisor vendor: Xen Virtualization type: full L1d cache: 32K L1i cache: 32K L2 cache: 256K L3 cache: 46080K NUMA node0 CPU(s): 0-15 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch cpuid_fault invpcid_single pti fsgsbase bmi1 hle avx2 smep bmi2 erms invpcid rtm rdseed adx xsaveopt

Versions of relevant libraries: [pip3] mypy-extensions==1.0.0 [pip3] numpy==1.26.4 [pip3] nvidia-nccl-cu12==2.19.3 [pip3] torch==2.2.1 [pip3] triton==2.2.0 [pip3] vllm-nccl-cu12==2.18.1.0.4.0 [conda] numpy 1.26.4 pypi_0 pypi [conda] nvidia-nccl-cu12 2.19.3 pypi_0 pypi [conda] torch 2.2.1 pypi_0 pypi [conda] triton 2.2.0 pypi_0 pypi [conda] vllm-nccl-cu12 2.18.1.0.4.0 pypi_0 pypiROCM Version: Could not collect Neuron SDK Version: N/A vLLM Version: N/A vLLM Build Flags: CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled GPU Topology: GPU0 CPU Affinity NUMA Affinity GPU NUMA ID^[[0m GPU0 X 0-15 0 N/A

Legend:

X = Self SYS = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI) NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node PHB = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU) PXB = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge) PIX = Connection traversing at most a single PCIe bridge NV# = Connection traversing a bonded set of # NVLinks

How you are installing vllm

pip install -e .

[fxavier-maf]

Running this on a g3.4xlarge instance.

[youkaichao]

Please read https://docs.vllm.ai/en/latest/getting_started/installation.html :

GPU: compute capability 7.0 or higher (e.g., V100, T4, RTX20xx, A100, L4, H100, etc.)

According to https://developer.nvidia.com/cuda-gpus , Tesla M60 's compute capability is 5.2 .

[fxavier-maf]

Thank you @youkaichao. Discovered later that, AWS instance compute capability is available at this URL - https://handbook.vantage.sh/aws/reference/aws-gpu-instances/

This can be combined with Vantage-sh to zero-in on the ideal EC2 instance.

[MGloder]

Hi @youkaichao, im using Geforce RTX 4090, facing the same issue and just double check the docs, it have 8.9; do you know why? can we reopen this issue? thanks!

[MGloder]

here is the error message:

ptxas /tmp/tmpxft_0000df54_00000000-6_attention_kernels.ptx, line 4984145; error   : Feature 'f16 arithemetic and compare instructions' requires .target sm_53 or higher
      ptxas /tmp/tmpxft_0000df54_00000000-6_attention_kernels.ptx, line 4984149; error   : Feature 'f16 arithemetic and compare instructions' requires .target sm_53 or higher
      ptxas /tmp/tmpxft_0000df54_00000000-6_attention_kernels.ptx, line 4984153; error   : Feature 'f16 arithemetic and compare instructions' requires .target sm_53 or higher
      ptxas /tmp/tmpxft_0000df54_00000000-6_attention_kernels.ptx, line 4984157; error   : Feature 'f16 arithemetic and compare instructions' requires .target sm_53 or higher
      ptxas fatal   : Ptx assembly aborted due to errors
      ninja: build stopped: subcommand failed.
      Traceback (most recent call last):
        File "/tmp/pip-build-env-vqjir97l/overlay/lib/python3.10/site-packages/setuptools/command/editable_wheel.py", line 135, in run
          self._create_wheel_file(bdist_wheel)
        File "/tmp/pip-build-env-vqjir97l/overlay/lib/python3.10/site-packages/setuptools/command/editable_wheel.py", line 338, in _create_wheel_file
          files, mapping = self._run_build_commands(dist_name, unpacked, lib, tmp)
        File "/tmp/pip-build-env-vqjir97l/overlay/lib/python3.10/site-packages/setuptools/command/editable_wheel.py", line 261, in _run_build_commands
          self._run_build_subcommands()
        File "/tmp/pip-build-env-vqjir97l/overlay/lib/python3.10/site-packages/setuptools/command/editable_wheel.py", line 288, in _run_build_subcommands
          self.run_command(name)
        File "/tmp/pip-build-env-vqjir97l/overlay/lib/python3.10/site-packages/setuptools/_distutils/cmd.py", line 316, in run_command
          self.distribution.run_command(command)
        File "/tmp/pip-build-env-vqjir97l/overlay/lib/python3.10/site-packages/setuptools/dist.py", line 948, in run_command
          super().run_command(command)
        File "/tmp/pip-build-env-vqjir97l/overlay/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 983, in run_command
          cmd_obj.run()
        File "/tmp/pip-build-env-vqjir97l/overlay/lib/python3.10/site-packages/setuptools/command/build_ext.py", line 96, in run
          _build_ext.run(self)
        File "/tmp/pip-build-env-vqjir97l/overlay/lib/python3.10/site-packages/setuptools/_distutils/command/build_ext.py", line 359, in run
          self.build_extensions()
        File "<string>", line 234, in build_extensions
        File "/home/machinedoll-t8/anaconda3/envs/vllm/lib/python3.10/subprocess.py", line 369, in check_call
          raise CalledProcessError(retcode, cmd)
      subprocess.CalledProcessError: Command '['cmake', '--build', '.', '-j=28', '--target=_core_C', '--target=_moe_C', '--target=_C']' returned non-zero exit status 1.
      /tmp/pip-build-env-vqjir97l/overlay/lib/python3.10/site-packages/setuptools/_distutils/dist.py:983: _DebuggingTips: Problem in editable installation.
      !!

[MGloder]

the output of python collect_env.py

Collecting environment information...
PyTorch version: N/A
Is debug build: N/A
CUDA used to build PyTorch: N/A
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.4 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: version 3.22.1
Libc version: glibc-2.35

Python version: 3.10.14 (main, May  6 2024, 19:42:50) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-6.8.0-40-generic-x86_64-with-glibc2.35
Is CUDA available: N/A
CUDA runtime version: 12.2.91
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 4090
Nvidia driver version: 535.183.01
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: N/A

CPU:
Architecture:                         x86_64
CPU op-mode(s):                       32-bit, 64-bit
Address sizes:                        39 bits physical, 48 bits virtual
Byte Order:                           Little Endian
CPU(s):                               28
On-line CPU(s) list:                  0-27
Vendor ID:                            GenuineIntel
Model name:                           Intel(R) Core(TM) i7-14700KF
CPU family:                           6
Model:                                183
Thread(s) per core:                   2
Core(s) per socket:                   20
Socket(s):                            1
Stepping:                             1
CPU max MHz:                          5600.0000
CPU min MHz:                          800.0000
BogoMIPS:                             6835.20
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 est tm2 ssse3 sdbg fma cx16 xtpr pdcm sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb intel_pt sha_ni xsaveopt xsavec xgetbv1 xsaves split_lock_detect user_shstk avx_vnni dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp hwp_pkg_req hfi vnmi umip pku ospke waitpkg gfni vaes vpclmulqdq rdpid movdiri movdir64b fsrm md_clear serialize arch_lbr ibt flush_l1d arch_capabilities
Virtualization:                       VT-x
L1d cache:                            768 KiB (20 instances)
L1i cache:                            1 MiB (20 instances)
L2 cache:                             28 MiB (11 instances)
L3 cache:                             33 MiB (1 instance)
NUMA node(s):                         1
NUMA node0 CPU(s):                    0-27
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: Mitigation; Clear Register File
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] No relevant packages
[conda] No relevant packages
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: N/A
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
GPU0    CPU Affinity    NUMA Affinity   GPU NUMA ID
GPU0     X      0-27    0               N/A

Legend:

  X    = Self
  SYS  = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI)
  NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node
  PHB  = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU)
  PXB  = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge)
  PIX  = Connection traversing at most a single PCIe bridge
  NV#  = Connection traversing a bonded set of # NVLinks

[MGloder]

problem solved; i was setting the cmake_cuda_architectures=native then if it will compile with sm_89; but the cuda eat all my CPU since i forget to set the max_job env var ...

[KungFuPandaPro]

problem solved; i was setting the cmake_cuda_architectures=native then if it will compile with sm_89; but the cuda eat all my CPU since i forget to set the max_job env var ...

what is the order? how to use cmake_cuda_architectures=native