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HGPU group
Сталкер Commander1024Ich habe den binären Vanilla #Blender (4.5.0) dazu bekommen, mittels #OneAPI mit der Intel Arc GPU der Notebook APU unter Fedora Linux zu rendern. \o/
Christos Argyropoulos MD, PhDUpdate on my #retroHPCcomputing project: it seems the first pcie slot is dead, but the X99 mobo has 7 slots, so this is not a big deal. Shown also the #XeonPhi the old Tesla #Nvidia c2075, the gt960 with its riser cable (prior to vertical install on the enthoo 719 case) & the RAID array.
I opted for Centos 7.3 as an initial choice to compile the Phi stack (will likely move to Alma 8 as I found instructions to compile the stack on CentOs 8 relatives). Hopefully, I have #OneApi 2021.2 somewhere
I opted for Centos 7.3 as an initial choice to compile the Phi stack (will likely move to Alma 8 as I found instructions to compile the stack on CentOs 8 relatives). Hopefully, I have #OneApi 2021.2 somewhere
Christos ArgyropoulosUpdate on my #retroHPCcomputing project: it seems the first pcie slot is dead, but the X99 mobo has 7 slots, so this is not a big deal. Shown also the #XeonPhi the old Tesla #Nvidia c2075, the gt960 with its riser cable (prior to vertical install on the enthoo 719 case) & the RAID array.
I opted for Centos 7.3 as an initial choice to compile the Phi stack (will likely move to Alma 8 as I found instructions to compile the stack on CentOs 8 relatives). Hopefully, I have #OneApi 2021.2 somewhere
I opted for Centos 7.3 as an initial choice to compile the Phi stack (will likely move to Alma 8 as I found instructions to compile the stack on CentOs 8 relatives). Hopefully, I have #OneApi 2021.2 somewhere
Thesis: Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing
Giuseppe BilottaEven now, Thrust as a dependency is one of the main reason why we have a #CUDA backend, a #HIP / #ROCm backend and a pure #CPU backend in #GPUSPH, but not a #SYCL or #OneAPI backend (which would allow us to extend hardware support to #Intel GPUs). <https://doi.org/10.1002/cpe.8313>
This is also one of the reason why we implemented our own #BLAS routines when we introduced the semi-implicit integrator. A side-effect of this choice is that it allowed us to develop the improved #BiCGSTAB that I've had the opportunity to mention before <https://doi.org/10.1016/j.jcp.2022.111413>. Sometimes I do wonder if it would be appropriate to “excorporate” it into its own library for general use, since it's something that would benefit others. OTOH, this one was developed specifically for GPUSPH and it's tightly integrated with the rest of it (including its support for multi-GPU), and refactoring to turn it into a library like cuBLAS is
a. too much effort
b. probably not worth it.
Again, following @eniko's original thread, it's really not that hard to roll your own, and probably less time consuming than trying to wrangle your way through an API that may or may not fit your needs.
6/