I am using nvfortran 23.11 and Cuda 12.3 - just updated both. Previously, I was able to use cudaGetDeviceProperties as in: istat = cudaGetDeviceProperties(prop, 0) if(istat /= cudaSuccess) then write(,) ‘GetDe
Hi, We are interesting in building our code with single-pass CUDA compilation usingnvc++ -cuda. We have replaced all usage of__CUDA_ARCH__with the portable NV_IF_TARGET macros. Using NVC++ 23.9, the code successfully builds withnvc++ -cuda, but we get device linker errors for device...
[ 0.4615, 0.3593, 0.5813, ..., -0.0779, -0.0349, 0.1422], ..., [ 0.1914, 0.6038, 0.0382, ..., -0.2847, -0.0991, -0.0423], [ 0.0864, 0.2895, 0.2719, ..., -0.2388, 0.0772, -0.1541], [ 0.2019, 0.2275, 0.9027, ..., 0.1022, 0.1300, 0.1444]], device='cuda:0', grad_fn=<...
1. Using Inline PTX Assembly in CUDA The NVIDIA® CUDA® programming environment provides a parallel thread execution (PTX) instruction set architecture (ISA) for using the GPU as a data-parallel computing device. For more information on the PTX ISA, refer to the latest version of ...
Chapter 33. LCP Algorithms for Collision Detection Using CUDA Peter Kipfer Havok An environment that behaves correctly physically is central to the immersive experience of a computer game. In some games, the player is even forced to interact with objects in the scene in a wa...
iftorch.cuda.is_available():dev="cuda:0"else:dev="cpu"device=torch.device(dev)a=torch.zeros(4,3)a=a.to(device)#alternatively, a.to(0) Copy You can also move a tensor to a certain GPU by giving it’s index as the argument totofunction. ...
Chapter 37. Efficient Random Number Generation and Application Using CUDA Lee Howes Imperial College London David Thomas Imperial College London Monte Carlo methods provide approximate numerical solutions to problems that would be difficult or impossible to solve exactly. The defining chara...
} else { __syncwarp (); v = __shfl (0); __syncwarp (); } 其次, 即使所有线程一起调用该序列, CUDA 执行模型也不能保证线程在离开 __syncwarp () 后保持收敛, 如清单 14 所示。 请记住, CUDA 不保证隐式的同步执行, 线程汇聚只在明确的 warp-level 同步原语内得到保证。 assert (__...
Device: cuda:0 AMD Radeon RX 6600 : native VAE dtype: torch.float32 Using sub quadratic optimization for cross attention, if you have memory or speed issues try using: --attention-split Refiner unloaded. model_type EPS UNet ADM Dimension 2816 ...
0 std::string paddle::platform::GetTraceBackString<char const*>(char const*&&, char const*, int) 1 paddle::platform::EnforceNotMet::EnforceNotMet(std::__exception_ptr::exception_ptr, char const*, int) 2 paddle::platform::GetCUDADeviceCount() ...