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Comment by _hzrk | Hacker News Reader

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.

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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.

> Seriously now, how many people from JVM or CLR world actually need this level of high performance?

The big data ecosystem is Java-centric.

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++.

Finance too, large exchanges with micro second latency have their core systems written in Java, CME Globex and EBS/Brokertec are written in Java.

Whenever I hit AI limits, it's due to memory. That's why I would argue the future of AI is Rust, not C++. Memory efficiency matters!

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