SYCL is the natively polyglot counterpart, with practical implementations of it compiling down to the same sort of SPIR-V kernels as OpenCL. (OTOH, much of the current adoption on the open standards side seems to target the more widely supported SPIR-V compute shaders, via Vulkan compute.)
Not really, first of all it is for C++, not the range of languages supported by CUDA.
Before SPIR was a thing in OpenCL, Khronos could not understand why anyone would care about anything else other than C99, or why supporting Fortran on GPUs was at all relevant.
Secondly, from the competition only Intel cares about SYCL with their own sugar on top, OpenAPI.
AMD hasn't cared one second about it.
You may mention Codeplay, which is anyway an Intel owned company since 2022.
As for Vulkan, it doesn't have neither the features, nor the tooling that CUDA enjoys, it is the usual putting up with using LEGOs from different brands, with various pin sizes, that is so common with Khronos.
SYCL is the natively polyglot counterpart, with practical implementations of it compiling down to the same sort of SPIR-V kernels as OpenCL. (OTOH, much of the current adoption on the open standards side seems to target the more widely supported SPIR-V compute shaders, via Vulkan compute.)
Not really, first of all it is for C++, not the range of languages supported by CUDA.
Before SPIR was a thing in OpenCL, Khronos could not understand why anyone would care about anything else other than C99, or why supporting Fortran on GPUs was at all relevant.
Secondly, from the competition only Intel cares about SYCL with their own sugar on top, OpenAPI.
AMD hasn't cared one second about it.
You may mention Codeplay, which is anyway an Intel owned company since 2022.
As for Vulkan, it doesn't have neither the features, nor the tooling that CUDA enjoys, it is the usual putting up with using LEGOs from different brands, with various pin sizes, that is so common with Khronos.