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
jeejeelee
commented
2 months ago
Your current environment
PyTorch version: 2.4.0 Is debug build: False CUDA used to build PyTorch: 12.1 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 3.29.5 Libc version: glibc-2.35
Python version: 3.11.9 (main, Apr 19 2024, 16:48:06) [GCC 11.2.0] (64-bit runtime) Python platform: Linux-6.8.0-40-generic-x86_64-with-glibc2.35 Is CUDA available: True CUDA runtime version: 12.1.105 CUDA_MODULE_LOADING set to: LAZY GPU models and configuration: GPU 0: NVIDIA RTX A6000 GPU 1: NVIDIA RTX A6000 GPU 2: NVIDIA RTX A6000 GPU 3: NVIDIA RTX A6000
Nvidia driver version: 560.28.03 cuDNN version: Could not collect HIP runtime version: N/A MIOpen runtime version: N/A Is XNNPACK available: True
CPU: 架构： x86_64 CPU 运行模式： 32-bit, 64-bit Address sizes: 43 bits physical, 48 bits virtual 字节序： Little Endian CPU: 256 在线 CPU 列表： 0-255 厂商 ID： AuthenticAMD 型号名称： AMD EPYC 7H12 64-Core Processor CPU 系列： 23 型号： 49 每个核的线程数： 2 每个座的核数： 64 座： 2 步进： 0 Frequency boost: enabled CPU 最大 MHz： 2600.0000 CPU 最小 MHz： 1500.0000 BogoMIPS： 5190.46 标记： 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 mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca sev sev_es 虚拟化： AMD-V L1d 缓存： 4 MiB (128 instances) L1i 缓存： 4 MiB (128 instances) L2 缓存： 64 MiB (128 instances) L3 缓存： 512 MiB (32 instances) NUMA 节点： 2 NUMA 节点0 CPU： 0-63,128-191 NUMA 节点1 CPU： 64-127,192-255 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: Mitigation; untrained return thunk; SMT enabled with STIBP protection Vulnerability Spec rstack overflow: Mitigation; Safe RET 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; Retpolines; IBPB conditional; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Not affected
Versions of relevant libraries: [pip3] numpy==1.26.4 [pip3] nvidia-nccl-cu11==2.20.5 [pip3] nvidia-nccl-cu12==2.20.5 [pip3] onnxruntime-gpu==1.16.0 [pip3] pytorch-lightning==2.3.3 [pip3] pyzmq==26.0.3 [pip3] torch==2.4.0 [pip3] torchaudio==2.4.0 [pip3] torchmetrics==1.4.0.post0 [pip3] torchvision==0.19.0 [pip3] transformers==4.43.2 [pip3] triton==2.3.1 [conda] blas 1.0 mkl
[conda] ffmpeg 4.3 hf484d3e_0 pytorch [conda] libjpeg-turbo 2.0.0 h9bf148f_0 pytorch [conda] mkl 2023.1.0 h213fc3f_46344
[conda] mkl-service 2.4.0 py311h5eee18b_1
[conda] mkl_fft 1.3.8 py311h5eee18b_0
[conda] mkl_random 1.2.4 py311hdb19cb5_0
[conda] numpy 1.26.4 py311h08b1b3b_0
[conda] numpy-base 1.26.4 py311hf175353_0
[conda] nvidia-nccl-cu11 2.20.5 pypi_0 pypi [conda] nvidia-nccl-cu12 2.20.5 pypi_0 pypi [conda] pytorch 2.4.0 py3.11_cuda12.1_cudnn9.1.0_0 pytorch [conda] pytorch-cuda 12.1 ha16c6d3_5 pytorch [conda] pytorch-lightning 2.3.3 pypi_0 pypi [conda] pytorch-mutex 1.0 cuda pytorch [conda] pyzmq 26.0.3 pypi_0 pypi [conda] torch 2.3.1 pypi_0 pypi [conda] torchaudio 2.4.0 py311_cu121 pytorch [conda] torchmetrics 1.4.0.post0 pypi_0 pypi [conda] torchtriton 3.0.0 py311 pytorch [conda] torchvision 0.18.1+cu118 pypi_0 pypi [conda] transformers 4.43.2 pypi_0 pypi [conda] triton 2.3.1 pypi_0 pypi ROCM Version: Could not collect Neuron SDK Version: N/A vLLM Version: 0.5.4@4db5176d9758b720b05460c50ace3c01026eb158 vLLM Build Flags: CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled GPU Topology: GPU0 GPU1 GPU2 GPU3 CPU Affinity NUMA Affinity GPU NUMA ID GPU0 X NV4 SYS SYS 0-63,128-191 0 N/A GPU1 NV4 X SYS SYS 0-63,128-191 0 N/A GPU2 SYS SYS X NV4 64-127,192-255 1 N/A GPU3 SYS SYS NV4 X 64-127,192-255 1 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 would you like to use vllm
vllm怎么开启并发