# All required CUDA packages
cuda-compat-12-1
cuda-command-line-tools-12-1
cuda-cudart-dev-12-1
cuda-nvcc-12-1
cuda-cupti-12-1
cuda-nvprune-12-1
cuda-libraries-12-1
cuda-libraries-dev-12-1
cuda-nvml-dev-12-1
libcufft-12-1
libcurand-12-1
libcusolver-dev-12-1
libcusparse-dev-12-1
libcublas-12-1
libcublas-dev-12-1
libnccl-dev=2.18.3-1+cuda12.1
libnccl2=2.18.3-1+cuda12.1

# All required CUDA packages
cuda-compat-12-3
cuda-command-line-tools-12-3
cuda-cudart-dev-12-3
cuda-nvcc-12-3
cuda-cupti-12-3
cuda-nvprune-12-3
cuda-libraries-12-3
cuda-libraries-dev-12-3
cuda-nvml-dev-12-3
libcufft-12-3
libcurand-12-3
libcusolver-dev-12-3
libcusparse-dev-12-3
libcublas-12-3
libcublas-dev-12-3
libnccl-dev=2.19.3-1+cuda12.3
libnccl2=2.19.3-1+cuda12.3

Make sure you evaluate if the **benefits** for your use case compensate the **drawbacks**. 🤓

///

## GraphQL Libraries { #graphql-libraries }

Here are some of the **GraphQL** libraries that have **ASGI** support. You could use them with **FastAPI**:

* <a href="https://strawberry.rocks/" class="external-link" target="_blank">Strawberry</a> 🍓

# All required CUDA packages
cuda-compat-12-8
cuda-command-line-tools-12-8
cuda-cudart-dev-12-8
cuda-nvcc-12-8
cuda-cupti-12-8
cuda-nvprune-12-8
cuda-libraries-12-8
cuda-libraries-dev-12-8
cuda-nvml-dev-12-8
libcufft-12-8
libcurand-12-8
libcusolver-dev-12-8
libcusparse-dev-12-8
libcublas-12-8
libcublas-dev-12-8
libnccl-dev=2.25.1-1+cuda12.8
libnccl2=2.25.1-1+cuda12.8

# All required CUDA packages
cuda-compat-13-0
cuda-command-line-tools-13-0
cuda-cudart-dev-13-0
cuda-nvcc-13-0
cuda-cupti-13-0
cuda-nvprune-13-0
cuda-libraries-13-0
cuda-libraries-dev-13-0
cuda-nvml-dev-13-0
libcufft-13-0
libcurand-13-0
libcusolver-dev-13-0
libcusparse-dev-13-0
libcublas-13-0
libcublas-dev-13-0
libnccl-dev=2.27.7-1+cuda13.0
libnccl2=2.27.7-1+cuda13.0

# All required CUDA packages
cuda-compat-12-1
cuda-command-line-tools-12-1
cuda-cudart-dev-12-1
cuda-nvcc-12-1
cuda-cupti-12-1
cuda-nvprune-12-1
cuda-libraries-12-1
cuda-libraries-dev-12-1
cuda-nvml-dev-12-1
libcufft-12-1
libcurand-12-1
libcusolver-dev-12-1
libcusparse-dev-12-1
libcublas-12-1
libcublas-dev-12-1
libnccl-dev=2.18.3-1+cuda12.1
libnccl2=2.18.3-1+cuda12.1

            // - Testing basic RDMA operations
            // - Checking for required native libraries

            return true;
        } catch (ClassNotFoundException e) {
            log.debug("DiSNI not available: {}", e.getMessage());
            return false;
        } catch (UnsatisfiedLinkError e) {
            log.debug("DiSNI native libraries not available: {}", e.getMessage());
            return false;
        }
    }

# packages only provide the "0.10-2build1" version. We use patchelf to manipulate
# certain shared libraries during the wheel building process (https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/pip_package/build_pip_package.sh#L255-L262).
# When we use Patchelf versions <0.12, those shared libraries end up with a

[![GitHub Release](https://img.shields.io/github/v/release/google/guava)](https://github.com/google/guava/releases/latest)
[![CI](https://github.com/google/guava/actions/workflows/ci.yml/badge.svg)](https://github.com/google/guava/actions/workflows/ci.yml)
[![OpenSSF Best Practices](https://www.bestpractices.dev/projects/7197/badge)](https://www.bestpractices.dev/projects/7197)

    return this;
  }

  /**
   * Advances the ticker value by {@code duration}.
   *
   * @since 33.1.0 (but since 28.0 in the JRE <a
   *     href="https://github.com/google/guava#guava-google-core-libraries-for-java">flavor</a>)
   */
  @GwtIncompatible
  @J2ktIncompatible
  @CanIgnoreReturnValue
  @IgnoreJRERequirement // TODO: b/288085449 - Remove this once we use library-desugaring scents.