ggml_set_omp_threads

Directly calls omp_set_num_threads() to limit OpenMP parallelism.
Useful in tests to comply with CRAN policy on core usage.

Provides 'R' bindings to the 'GGML' tensor library for machine
learning, optimized for 'Vulkan' GPU acceleration with a transparent CPU
fallback. The package features a 'Keras'-like sequential API and a
'PyTorch'-style 'autograd' engine for building, training, and deploying
neural networks. Key capabilities include high-performance 5D tensor
operations, 'f16' precision, and efficient quantization. It supports
native 'ONNX' model import (50+ operators) and 'GGUF' weight loading
from the 'llama.cpp' and 'Hugging Face' ecosystems. Designed for
zero-overhead inference via dedicated weight buffering, it integrates
seamlessly as a 'parsnip' engine for 'tidymodels' and provides
first-class learners for the 'mlr3' framework.
See <https://github.com/ggml-org/ggml> for more information about the
underlying library.

Yuri Baramykov

ggmlR

'GGML' Tensor Operations for Machine Learning

ggml_set_omp_threads function

<dl><dt>n</dt>
<dd>Number of threads</dd></dl>

Arguments

Set OpenMP Thread Count — ggml_set_omp_threads

<dl>

<dt>n</dt>
<dd>Number of threads</dd>

</dl>

ggml_set_omp_threads: Set OpenMP Thread Count

Description

Usage

Value

Arguments