First introduced in 2014, SYCL is a C++ based heterogeneous parallel programming framework for accelerating High Performance Computing (HPC), machine learning, embedded computing, and compute-intensive desktop applications on a range of processor architectures, including CPUs, GPUs, FPGAs...
torch::Tensor tensor = torch::rand({2, 3}); std::cout << tensor << std::endl; return 0; //retun for main() } //ending main() Result & error: The compilation was successful. The link gives the following error (seems to be a problem with...
The sum operation uses the reorder primitive to sum tensors, so the same limitation as reorder applies here. ### Shuffle The shuffle primitive is implemented using SYCL kernels. This primitive supports both forward and backward propagations. * Supported formats: `NCDHW`, `NDHWC`, `NCHW`, `...
Describe the bug Hi, First apology for my probably poor comprehension of C++. In the reproducer below we create a templated anonymous class that will be used to create a name for our parallel_for. This code is not compiling and give a de...
However, as a programmer - I quickly realize that key parts of CPUs and IPUs are there to accelerate key algorithms like vector math, matrix math, tensor math, and crypto. So, while CPUs or IPUs are not simply XPUs, they incorporate accelerator (XPU) functionality so that targettting ...
摘要这篇文章介绍了使用MLIR编译器基础架构针对NVIDIA GPU上的Tensor Core生成代码的一些结果。当前高性能深度学习的最新技术主要由高度调优的库驱动。...因此,这个过程不像LLVM这样的编译器基础设施那样模块化以及可重用性很强。手工优化通常不使用IR,尽管这些优化可以被编码为一系列在IR上定义的pass。...在我们的实验...
Figure: Kernel performance using individual kernels versus kernel fusion Adding the SYCL Backend to Eigen When we began designing the integration of SYCL with Eigen, we wanted to ensure that the back-end implementation provided compatibility for existing frameworks that use the tensor operations. By ...
static std::array<float, GGML_SYCL_MAX_DEVICES> g_default_tensor_split = {}; Expand DownExpand Up@@ -13244,7 +13225,7 @@ void ggml_backend_sycl_print_sycl_devices() { } void print_gpu_device_list() { fprintf(stderr, "detect %d SYCL GPUs: [%s] withtopMax compute units:%d\n"...
get_queue * add print tensor function to debug * fix error: wrong result in 658746bb26702e50f2c59c0e4ada8e9da6010481 * summary dpct definition in one header file to replace folder:dpct * refactor device log * mv dpct definition from folder dpct to ggml-sycl.h * update readme, ...
Tensor library for machine learning. Contribute to Rimaan/ggml_jai development by creating an account on GitHub.