I really don't get this push to polyglot programming when 99% of the high performance libraries use C++. Even more, openAPI has DPC++, SPIR-V has SYCL, CUDA is even building a C++ standard library that is heterogeneous supporting both CPU and GPU, libcu++. Seriously now, how many people from JVM or CLR world actually need this level of high performance? How many actually push kernels to the GPU from these runtimes? I have yet to see a programming language that will replace C++ at what it does best. Maybe Zig because it is streamlined and easier to get into will be a true contender to C++ HPC but only time will tell.
Enough people to keep a couple of companies in business, and NVidia doing collaboration projects with Microsoft and Oracle, HPC is not the only market for CUDA.
Indeed it is, but the developers in these ecosystems created complements like Apache Arrow that will unload the data in a language-independent columnar memory format for efficient analytics in services that will run C++ on clusters of CPUs and GPUs. Even Spark has rewritten their own analytics engine in C++ recently. These were created because of the limitations of the JVM. We have tried to move the numerical processing away from C++ in the past decades but we have always failed.
You asked who in the JVM world would be interested in this kind of performance: that's big data folks. To the extent that improvements accrue to the JVM they accrue to that world without needing to rewrite into C++.
