As far as I understand you will need a GPU for each worker node or you will need to partition the GPU processing somehow to each node which I think would defeat the purpose. In Databricks for example when you select GPU workers there is a GPU allocated to each worker. I assume this is the “correct” approach to this problem
On Mon, 6 Feb 2023 at 8:17 AM, Mich Talebzadeh <mich.talebza...@gmail.com> wrote: > if you have several nodes with only one node having GPUs, you still have > to wait for the result set to complete. In other words it will be as fast > as the lowest denominator .. > > my postulation > > HTH > > > > view my Linkedin profile > <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/> > > > https://en.everybodywiki.com/Mich_Talebzadeh > > > > *Disclaimer:* Use it at your own risk. Any and all responsibility for any > loss, damage or destruction of data or any other property which may arise > from relying on this email's technical content is explicitly disclaimed. > The author will in no case be liable for any monetary damages arising from > such loss, damage or destruction. > > > > > On Sun, 5 Feb 2023 at 13:38, Irene Markelic <ir...@markelic.de> wrote: > >> Hello, >> >> has anyone used spark with GPUs? I wonder if every worker node in a >> cluster needs one GPU or if you can have several worker nodes of which >> only one has a GPU. >> >> Thank you! >> >> >> >> --------------------------------------------------------------------- >> To unsubscribe e-mail: user-unsubscr...@spark.apache.org >> >>
