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[95.118.110.69]) by smtp.gmail.com with ESMTPSA id q5-20020a056402248500b0055f48b49d05sm2029594eda.69.2024.02.03.11.38.13 (version=TLS1_3 cipher=TLS_AES_128_GCM_SHA256 bits=128/128); Sat, 03 Feb 2024 11:38:13 -0800 (PST) Content-Type: text/plain; charset=utf-8 Content-Transfer-Encoding: quoted-printable From: Richard Biener Mime-Version: 1.0 (1.0) Subject: Re: GPU offloading question Date: Sat, 3 Feb 2024 20:38:02 +0100 Message-Id: <87E7C31E-C475-49AB-BAB5-D33CC86A5F21@gmail.com> References: Cc: sgk@troutmask.apl.washington.edu, fortran@gcc.gnu.org In-Reply-To: To: Benson Muite X-Mailer: iPhone Mail (21D50) X-Spam-Status: No, score=-3.2 required=5.0 tests=BAYES_00,DKIM_SIGNED,DKIM_VALID,DKIM_VALID_AU,DKIM_VALID_EF,FREEMAIL_FROM,RCVD_IN_DNSWL_NONE,SPF_HELO_NONE,SPF_PASS,TXREP,T_SCC_BODY_TEXT_LINE autolearn=ham autolearn_force=no version=3.4.6 X-Spam-Checker-Version: SpamAssassin 3.4.6 (2021-04-09) on server2.sourceware.org List-Id: > Am 03.02.2024 um 19:15 schrieb Benson Muite : >=20 > =EF=BB=BFOn 03/02/2024 19.13, Steve Kargl wrote: >>> On Sat, Feb 03, 2024 at 02:37:05PM +0100, Richard Biener wrote: >>>=20 >>>> Am 03.02.2024 um 01:22 schrieb Steve Kargl : >>>>=20 >>>> All, >>>>=20 >>>> 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)? >>>=20 >>> You need the HSA runtime for AMD which comes with ROCm and libcuda >>> for NvIDIA which comes with CUDA. >>=20 >> 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 Support is likely non existent on FreeBSD since there=E2=80=99s a driver com= ponent as well. For modern GPUs the driver is open source in Linux for both= vendors but the firmware is not. CUDA is proprietary while the HSA runtime= part is easily built from source (it=E2=80=99s hosted on GitHub) >>> I=E2=80=99ve 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= . >>>=20 >>> I can=E2=80=99t say anything about performance with regard to how GCC ha= ndles both. >>>=20 >>> Note that double precision math performance is said to be severely >>> constrained for consumer hardware. >>=20 >> Ah, good point. I'll need to find a card I can afford that supports >> double precision. >>=20 >>=20 > 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. Yeah, I would also suggest development resources available as part of SC cen= ter access here. Richard=20=