#6743 [Core feature] Greater flexibility with GPUs accelerated workloads Issue created by Sovietaced ### Motivation: Why do you think this is important? Right now the configuration around GPU accelerated workloads is quite rigid. Flyte propeller only allows for a global GPU resource name to be configured which makes impossible to use Flyte with data planes that have heterogenous GPU resource vendors/names. Additionally, it is assumed that all GPU accelerated compute nodes will require a singular node selector label or taint key/value. In our environment our compute nodes contain multiple taints. We have worked around some of these issues using pod templates but we hit a blocker when we needed to support fractionalized GPUs with

<http://nvidia.com/gpu.shared|nvidia.com/gpu.shared>

. ### Goal: What should the final outcome look like, ideally? A more flexible configuration for GPU accelerated workloads where custom resource names, node selectors, and tolerations can be configured. ### Describe alternatives you've considered None ### Propose: Link/Inline OR Additional context No response ### Are you sure this issue hasn't been raised already? • Yes ### Have you read the Code of Conduct? • Yes flyteorg/flyte