The Xeon Phis really shit the bed on developer experience, so hopefully that experience has been taken to heart. The Xeon Phi marketing promise was basically "t

The Xeon Phis really shit the bed on developer experience, so hopefully that experience has been taken to heart. The Xeon Phi marketing promise was basically "take your existing parallel x86 code, run it in on more cores", with some massive caveats: - For the KNC generation, you had to compile with the Intel C/C++ compiler, which at the time cost $$$ and completely ruled out anyone who wasn't already a HPC developer or a student with access to free ICC. - The KNC PCIe card actually made a lot of sense hardware-wise, but ran really hot and needed water cooling for a bearable desktop experience. Of course, water cooling was only available late in the KNC cycle from third parties. The cheap KNC cards Intel made available for developers were passively cooled?! and clearly an afterthought. - The system software was abjectly horrible. The kernel driver required ridiculous patching if you weren't using the officially supported RedHat/CentOS variants, and the MPSS system software itself needed hacks and workarounds to install and configure. - The KNC environment was just bizarre. It was Linux, so you could SSH to the card and do things, but it didn't run normal x86 binaries. The interaction between offload modes and card configuration/security was basically guaranteed to break if you didn't follow every step of several dozen in the manual exactly, which of course could be a problem when the instructions were for RedHat/CentOS and you were using a different distro. The KNL generation was poised to solve a lot of these problems - bootable, properly supported by GCC - and then Intel gave up on the PCIe card and the only developer platform was like $20k and it was absolutely out of reach for anyone not already invested in the platform. I'm convinced that there were a large number of users who were interested in the platform, and would have been well-served by the programming model and performance, but the barrier to entry was just too high. Nvidia got this right from basically day 1 - CUDA was available at a range of price points with (roughly) the same capabilities, so a developer could have an idea, try it out and see the benefits. Throughout almost all of CUDA's existence, for the vast majority of applications you can conclusively answer if it will work for your problem by testing on a high-end consumer GPU that costs less than $1000. Intel never understood that then, hopefully they do now.