ggmlR (version 0.6.1)

ggml_backend_sched_graph_compute: Compute graph using scheduler

Description

Computes a graph by distributing work across multiple backends. This is the main function for multi-GPU computation.

Usage

ggml_backend_sched_graph_compute(sched, graph)

Value

Status code (0 = success)

Arguments

sched

Scheduler pointer

graph

Graph pointer

Examples

# \donttest{
# Multi-GPU example
if (ggml_vulkan_available() && ggml_vulkan_device_count() >= 2) {
  gpu1 <- ggml_vulkan_init(0)
  gpu2 <- ggml_vulkan_init(1)
  sched <- ggml_backend_sched_new(list(gpu1, gpu2))

  ctx <- ggml_init(64 * 1024 * 1024)
  a <- ggml_new_tensor_1d(ctx, GGML_TYPE_F32, 10000)
  b <- ggml_new_tensor_1d(ctx, GGML_TYPE_F32, 10000)
  ggml_set_f32(a, rnorm(10000))
  ggml_set_f32(b, rnorm(10000))

  c <- ggml_add(ctx, a, b)
  graph <- ggml_build_forward_expand(ctx, c)

  # Reserve memory
  ggml_backend_sched_reserve(sched, graph)

  # Compute using both GPUs
  ggml_backend_sched_graph_compute(sched, graph)

  result <- ggml_get_f32(c)

  cat("Splits:", ggml_backend_sched_get_n_splits(sched), "\n")
  cat("Copies:", ggml_backend_sched_get_n_copies(sched), "\n")

  ggml_free(ctx)
  ggml_backend_sched_free(sched)
  ggml_vulkan_free(gpu1)
  ggml_vulkan_free(gpu2)
}
# }