Isaac Gym - Training Ant ( nvrtc: error: invalid value for --gpu-architecture (-arch))

I download Isaac Gym from GitHub - NVIDIA-Omniverse/OmniIsaacGymEnvs: Reinforcement Learning Environments for Omniverse Isaac Gym, successfully run Cartpole example but can not run Ant. I have tried my best but could not solve the problem. Here are the infomation:

Error executing job with overrides: [‘task=Ant’]
Traceback (most recent call last):
File “scripts/”, line 201, in parse_hydra_configs
File “/home/lzy/.local/share/ov/pkg/isaac_sim-2022.1.1/exts/omni.isaac.gym/omni/isaac/gym/vec_env/”, line 195, in run
File “/home/lzy/.local/share/ov/pkg/isaac_sim-2022.1.1/exts/omni.isaac.core/omni/isaac/core/world/”, line 285, in reset
File “/home/lzy/桌面/OmniIsaacGymEnvs-main/omniisaacgymenvs/tasks/”, line 86, in post_reset
File “/home/lzy/桌面/OmniIsaacGymEnvs-main/omniisaacgymenvs/tasks/shared/”, line 178, in post_reset
File “/home/lzy/桌面/OmniIsaacGymEnvs-main/omniisaacgymenvs/tasks/shared/”, line 131, in reset_idx
dof_vel = torch_rand_float(-0.1, 0.1, (num_resets, self._robots.num_dof), device=self._device)
RuntimeError: nvrtc: error: invalid value for --gpu-architecture (-arch)

nvrtc compilation failed:

#define NAN __int_as_float(0x7fffffff)
#define POS_INFINITY __int_as_float(0x7f800000)
#define NEG_INFINITY __int_as_float(0xff800000)

device T maximum(T a, T b) {
return isnan(a) ? a : (a > b ? a : b);

device T minimum(T a, T b) {
return isnan(a) ? a : (a < b ? a : b);

extern “C” global
void fused_mul_add(double vlower_1, float* tv_, double vv__, float* aten_add) {
float v = ldg(tv + (long long)(threadIdx.x) + 512ll * (long long)(blockIdx.x));
aten_add[(long long)(threadIdx.x) + 512ll * (long long)(blockIdx.x)] = v * (float)(vv
_) + (float)(vlower_1);

Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.
/home/lzy/.local/share/ov/pkg/isaac_sim-2022.1.1/行 40: 5761 段错误 (核心已转储) $python_exe “$@” $args
There was an error running python

System and GPU info:
Ubuntu 22.04 LTS
NVIDIA-SMI 520.56.06
Driver Version: 520.56.06
CUDA Version: 11.8

Appreciate for your help QAQ

I have solved it! By install NVIDIA driver 525.53(beta). The problem comes from too low driver version.

I find that CUDA 11.8 need driver version >= 520.61.5, then I installed driver 525.53(beta) and it works. Using lower version CUDA like 11.7 may also work.