$ export CUDACXX=${CUDA_INSTALL_PATH}/bin/nvccCreate a build directory within the CUTLASS project, then run CMake. By default CUTLASS will build kernels for CUDA architecture versions 5.0, 6.0, 6.1, 7.0, 7.5, 8.0, 8.6, 8.9, and 9.0. To reduce compile time you can specify the ...
Last commit date Latest commit History 9 Commits detection figs segmentation LICENSE README.md README MIT license LinK: Linear Kernel for LiDAR-based 3D Perception Official PyTorch implementation ofLinK, from the following paper: LinK: Linear Kernel for LiDAR-based 3D Perception. CVPR 2023. ...
Computationally expensive matrix diagonalization and kernel image projections are programmed to run on massively parallel CUDA-enabled graphics processors, when available, giving an order of magnitude enhancement in computational speed. The software is available from the authors' Web sites.Morton J. Canty...
然后,在https://github.com/BBuf/how-to-optim-algorithm-in-cuda/blob/master/linear-attention/causal_product_cuda.cu#L661-L689对应的lmha模板函数的实现中有两种不同的kernel dispatch逻辑: // GO_BACKWARD: 一个布尔类型的模板参数,用于指示是进行前向计算还是反向计算。 template< bool GO_BACKWARD > in...
我们先从理论上来解释一下这个kernel的取名,cuda中occupancy指的是一个SM中实际活跃的warp与理论上可以最高可以活跃的warp的比值,然后如果occupancy太低直接带来的影响就是GPU没有足够多的warp来切换,就无法隐藏数据加载/计算的延时,直接导致了kernel B的算力下降。而触发这个lmha_low_occupancy_kernel的条件就是blocks...
另外,还会根据 query 的特征维度的大小 E 来设置kernel不同的模板参数。【BBuf的CUDA笔记】十,Linear Attention的cuda kernel实现解析详细解析了lmha_这个kernel的实现,这篇文章就来详解一下lmha_low_occupancy_的实现。 lmha_low_occupancy_ kernel实现解析...
Also, a small micro-optimization: skip the.item()call ontotal_n_non_ignore(the subsequent calculations work fine with the tensor form) to defer CUDA synchronization (otherwise it will wait for all thetorch.zerosinitializations on the preceding lines to synchronize, which may take a non-trivial...
pip install -r requirements.txt cd flash_linear_attention && FLA_SKIP_CUDA_BUILD=TRUE pip install -e .Fill missing Wandb key, entity and project ids in config files. Now you can start with running one simple MQAR experiment on sequence length 48:...
Efficient Triton Kernels for LLM Training. Contribute to linkedin/Liger-Kernel development by creating an account on GitHub.
solver CSVM class use, Plat SMO solver, LIBSVM solver, there are also few experimental solver, or you can implement and easily plug in your solver. Second you can choose different SVM kernels: Linear, RBF, CudaLinear, CudaRbf or you can implement IKernel interface and use your custom ...