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Intel’s OneAPI is already miles a head of AMD’s ROCm which is pretty awesome.


When? Where? How can it be miles ahead if the hardware has not been released yet?


Yes, seconding that.

What the point of using OneAPI, a yet another compute API wrapper, to make software just for a single platform?

You can just use regular computing libs, and C, or C++.

Serious HPC will still stay with its own serious HPC stuff, superoptimised C, and fortran code, no matter how labour intensive it is.

So, I see very little point in that.


OneAPI is already cross platform through codeplay’s implementation which also can run on NVIDIA GPUs, its whole point is to be open cross platform framework that targets a wide range of hardware.

Wether it would be successful or not is up in the air but it’s goals are pretty solid.


So basically, a thing that will provide first-class capabilities only on Intel hardware, and won't be really optimised for maximum performance/expose all the underlying capabilities of the hardware elsewhere.


Superoptimised C++, and Fortran code, with Chapel on the horizon.


Sadly, that's not a very high bar to set...


Now they need to catch up with polyglot CUDA eco-system.


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.


> 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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