From: Richard Biener <richard.guenther@gmail.com>
To: sgk@troutmask.apl.washington.edu
Cc: fortran@gcc.gnu.org
Subject: Re: GPU offloading question
Date: Sat, 3 Feb 2024 14:37:05 +0100 [thread overview]
Message-ID: <29F25227-C186-4B29-BC4D-6DC5EA038A71@gmail.com> (raw)
In-Reply-To: <Zb2HG0e7D3htyG_K@troutmask.apl.washington.edu>
> Am 03.02.2024 um 01:22 schrieb Steve Kargl <sgk@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. 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.
Richard
>
> --
> Steve
next prev parent reply other threads:[~2024-02-03 13:37 UTC|newest]
Thread overview: 6+ messages / expand[flat|nested] mbox.gz Atom feed top
2024-02-03 0:21 Steve Kargl
2024-02-03 13:37 ` Richard Biener [this message]
2024-02-03 16:13 ` Steve Kargl
2024-02-03 18:15 ` Benson Muite
2024-02-03 18:37 ` Steve Kargl
2024-02-03 19:38 ` Richard Biener
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