Tabulate dispatch plans across multiple operations

Runs amatrix_backend_plan for each requested operation and returns the results as a single data.frame, one row per operation. Useful for inspecting which backend will be used across an entire workload.

Usage

amatrix_backend_matrix(
  x,
  ops = c("matmul", "crossprod", "tcrossprod", "ewise", "rowSums", "colSums", "solve",
    "chol", "qr", "svd", "eigen", "diag"),
  y_map = list()
)

Arguments

x

An aMatrix object.

ops

Character vector of operation names. Defaults to the twelve standard operations.

y_map

Named list mapping operation names to right-hand-side objects. Use to supply a y argument for binary operations such as "matmul".

Value

A data.frame with one row per operation and columns:

op

Character. Operation name.

precision

Character. Precision mode.

pinned_backend

Character. Backend to which x is GPU-resident, or NA.

preferred

Character. Preference order string.

chosen

Character. Selected backend.

chosen_path

Character. "resident" or "cold".

resident_reuse

Logical. Whether the resident path is active.

cpu_fallback

Logical. Whether CPU was chosen despite not being first preference.

candidate_summary

Character. Compact flag string for all candidates.

See also

amatrix_backend_plan, amatrix_execution_info

Examples

m <- adgeMatrix(matrix(1:6, 2, 3))
amatrix_backend_matrix(m, ops = c("matmul", "crossprod"))
#>          op precision pinned_backend preferred chosen chosen_path
#> 1    matmul    strict           <NA>       cpu    cpu        cold
#> 2 crossprod    strict           <NA>       cpu    cpu        cold
#>   resident_reuse cpu_fallback candidate_summary
#> 1          FALSE        FALSE    cpu[RAP-C-KSX]
#> 2          FALSE        FALSE    cpu[RAP-C-KSX]