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MMA-optimized batched MRHS MG #1540
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…r operators; delay enablement of MMA in transfer until after coarse operator is computed to avoid double storage of V in MMA order; only store V in native or MMA order to reduce memory
…rn_residual, use_init_guess. These can now be updated using the Solver::update_param interface
…mer for the latter to reduce memory consumption
… This is helpful for unform object creation.
…lied using tensor cores
…ngle MMA-ordered super-system: prolongator, restrictor and dslash coarse will now not reorder if the input / output fields are already in the correct order
…ith a ColorSpinorField; deploy this to check if we need to nuke any preexisting allications when resizing std::vector<ColorSpinorField>
…eferences around the input (useful for creating a uniform code path between native and MMA ordered solvers)
…ew parameter QudaMultigridParam::collapse_mrhs enables this on a per level basis, with MMA enablement for both dslash and transfer operator (on the finer level) required; deflation is presently handled by expanding the collapsed space to the batch form, and then collapsing again post deflation. This removes all the BlockTranspose operations outside of the initial coarsening and final prolongation (deflation excepting).
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…this fixes the verify routine with MMA transfer routines when using half precision
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…-misc
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This PR focuses on improving the use of MMA with batched multigrid, resulting in the optimal MRHS multigrid performance:
QudaMultigridParam::collapse_mrhs
(--mg-collapse-mrhs
from the command line)vector_ref<ColorSpinorField>::size_actual()
to allow us to query the number of RHS in a collapsed systemFieldTmp
BlockTranspose
input field set can now be in half precision