From 88841c0d32a6feab9641c6aba00b930b289caa31 Mon Sep 17 00:00:00 2001 From: Ralph Liu Date: Mon, 13 Jan 2025 11:45:34 -0800 Subject: [PATCH] Rewording --- docs/cugraph-docs/source/nx_cugraph/benchmarks.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/cugraph-docs/source/nx_cugraph/benchmarks.rst b/docs/cugraph-docs/source/nx_cugraph/benchmarks.rst index 2f6231c..58019ea 100644 --- a/docs/cugraph-docs/source/nx_cugraph/benchmarks.rst +++ b/docs/cugraph-docs/source/nx_cugraph/benchmarks.rst @@ -3,7 +3,7 @@ Benchmarks This page presents the performance of algorithms currently supported by ``nx-cugraph`` across four graphs of varying sizes. -The goal is to provide a clear comparison of how dispatching to a GPU-accelerated backend compares against the default, CPU-based implementation of NetworkX. This allows users to get an idea of potential speedups that they might gain from leveraging dispatching to a GPU with ``nx-cugraph``. +The goal is to provide a clear comparison of how dispatching to a GPU-accelerated backend compares against the default, CPU-based implementation of NetworkX. This allows users to get an idea of potential speedups that they might see by leveraging dispatching to a GPU with ``nx-cugraph``. As datasets grow larger, the GPU-accelerated backend begins to show increasingly faster speedups over the CPU. This trend demonstrates how the GPU's parallel processing capabilities allow it to handle large-scale graph analytics much more efficiently than the CPU.