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Matrix product on a chosen 'GGML' backend

Source: R/rggml_mul_mat.R
rggml_mul_mat.Rd

Computes crossprod(A, B) (that is t(A) %*% B) through 'GGML' on the requested backend, using the backend-agnostic residency path: the operands and result are allocated in one of the backend's own buffers, the inputs uploaded, the product computed, and the result downloaded. For a GPU backend the tensors live in device memory, so this is the entry point a caller uses to run a dense single-precision GEMM on the GPU.

Usage

rggml_mul_mat(A, B, backend = c("cpu", "blas", "vulkan"))

Arguments

A, B

Numeric matrices with the same number of rows (the contracted dimension). Computed in single precision on every backend.

backend

One of "cpu" (ggml_backend_cpu_init()), "blas" (offloads the dense F32 product to whatever BLAS the R build links against), or "vulkan" (a Vulkan device; requires Rggml built with --with-vulkan and a visible device, see rggml_vulkan_info()). Errors if the requested backend is unavailable.

Value

A numeric matrix, dim c(ncol(A), ncol(B)), equal to crossprod(A, B) up to single-precision rounding.

See also

rggml_vulkan_info(), rggml_cpu_info()

Examples

A <- matrix(rnorm(12), 4, 3)
B <- matrix(rnorm(8), 4, 2)
rggml_mul_mat(A, B)               # == crossprod(A, B) to fp32
#>           [,1]       [,2]
#> [1,] -4.546084 -0.6009226
#> [2,] -1.062304 -1.1480335
#> [3,] -1.498720 -0.7332473