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Co-authored-by: Bradley Dice <bdice@bradleydice.com>

.github/workflows/build-test-publish-images.yml

@@ -101,7 +101,7 @@ jobs:
         run: |
           base_repo="base"
           notebooks_repo="notebooks"
-          CUVS_bench_repo="cuvs-bench"
+          cuvs_bench_repo="cuvs-bench"
           CUVS_bench_datasets_repo="cuvs-bench-datasets"
           CUVS_bench_cpu_repo="cuvs-bench-cpu"
           if [ "${{ inputs.build_type }}" = "pull-request" ]; then

context/cuvs-bench/get_datasets.sh

@@ -1,5 +1,5 @@
 #!/bin/bash
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2024, NVIDIA CORPORATION.
 
 set -eo pipefail
 

cuvs-bench/README.md

@@ -1,8 +1,8 @@
-# cuvs ANN Benchmarks docker
+# cuVS Benchmarks Docker Images
 
-This folder contains the dockerfiles for generating GPU and CPU cuvs ANN benchmark images.
+This folder contains the Dockerfiles for generating GPU and CPU cuVS benchmark images.
 
-These images are meant to enable end users of cuvs's ANN algorithms to easily run and reproduce benchmarks and comparisons between cuvs and third party libraries.
+These images are meant to enable end users of cuVS ANN algorithms to easily run and reproduce benchmarks and comparisons between cuVS and third party libraries.
 
 # Image types:
 
@@ -13,15 +13,15 @@ There are two image types:
 
 # Running the Containers
 
-For complete details, refer to cuVS's documentation https://docs.rapids.ai/api/cuvs/nightly/cuvs_bench/#installing-the-benchmarks.
+For complete details, refer to the cuVS documentation: https://docs.rapids.ai/api/cuvs/nightly/cuvs_bench/#installing-the-benchmarks
 
 We provide images for GPU enabled systems, as well as systems without a GPU. The following images are available:
 
 - `cuvs-bench`: Contains GPU and CPU benchmarks, can run all algorithms supported. Will download million-scale datasets as required. Best suited for users that prefer a smaller container size for GPU based systems. Requires the NVIDIA Container Toolkit to run GPU algorithms, can run CPU algorithms without it.
 - `cuvs-bench-datasets`: Contains the GPU and CPU benchmarks with million-scale datasets already included in the container. Best suited for users that want to run multiple million scale datasets already included in the image.
 - `cuvs-bench-cpu`: Contains only CPU benchmarks with minimal size. Best suited for users that want the smallest containers to reproduce benchmarks on systems without a GPU.
 
-Nightly images are located in [dockerhub](https://hub.docker.com/r/rapidsai/cuvs-bench), meanwhile release (stable) versions are located in [NGC](https://hub.docker.com/r/rapidsai/cuvs-bench), starting with release 23.12.
+Nightly images are located in [DockerHub](https://hub.docker.com/r/rapidsai/cuvs-bench), meanwhile release (stable) versions are located in [NGC](https://hub.docker.com/r/rapidsai/cuvs-bench).
 
 ## Container Usage
 

cuvs-bench/cpu/Dockerfile

@@ -3,7 +3,7 @@
 ARG PYTHON_VER=unset
 ARG RAPIDS_VER=24.12
 
-FROM condaforge/mambaforge:23.3.1-0 AS cuvs-bench-cpu
+FROM condaforge/miniforge3:24.7.1-2 AS cuvs-bench-cpu
 ARG RAPIDS_VER
 ARG PYTHON_VER