On 03/02/2024 19.13, Steve Kargl wrote:
> On Sat, Feb 03, 2024 at 02:37:05PM +0100, Richard Biener wrote:
>>
>>> Am 03.02.2024 um 01:22 schrieb Steve Kargl
>>> <s...@troutmask.apl.washington.edu>:
>>>
>>> All,
>>>
>>> Suppose one is working in a funding-constrained environment
>>> such as an academician with limited grant funding. If one
>>> wanted to dabble in GPU offloading with gcc/gfortran, what
>>> recommendations would one have for minimum required hardware?
>>> In addition, are there any vendor software layers that are
>>> required (such as AMD ROCm with an AMD GPU)?
>>
>> You need the HSA runtime for AMD which comes with ROCm and libcuda
>> for NvIDIA which comes with CUDA.
>
> Thanks. I'll need to check the level of support for the above
> in FreeBSD. I suspect it's non-existent, so looks like I'll take
> a plunge down the linux rabbit hole.
>
>> I’ve had success getting both a very low end gtx1650 and a high
>> end rx6900xt running with simple offloading. The officially supported
>> set of hardware is way bigger with CUDA when it comes to lower end cards.
>>
>> I can’t say anything about performance with regard to how GCC handles both.
>>
>> Note that double precision math performance is said to be severely
>> constrained for consumer hardware.
>
> Ah, good point. I'll need to find a card I can afford that supports
> double precision.
>
>
Consider https://allocations.access-ci.org/resources
for a PI based in the USA. Use the limited funding to support your time
improving off loading support for GFortran.
