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Test CCCL 3.2.x #20723

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Test CCCL 3.2.x #20723

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b0daef5
Update to CCCL 3.2.x
bdice Nov 21, 2025
9783ba9
Refactors needed for CCCL 3.2 compatibility.
bdice Dec 8, 2025
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2 changes: 2 additions & 0 deletions cmake/rapids_config.cmake
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Original file line number Diff line number Diff line change
Expand Up @@ -4,6 +4,8 @@
# SPDX-License-Identifier: Apache-2.0
# cmake-format: on
# =============================================================================
set(rapids-cmake-repo bdice/rapids-cmake)
set(rapids-cmake-branch cccl-3.2.x)
Comment on lines +7 to +8
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@bdice bdice Nov 25, 2025

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This is pinned to CCCL v3.2.0-rc0 and a custom commit hash of RMM that I believe is sufficient to make cuDF build.

file(READ "${CMAKE_CURRENT_LIST_DIR}/../VERSION" _rapids_version)
if(_rapids_version MATCHES [[^([0-9][0-9])\.([0-9][0-9])\.([0-9][0-9])]])
set(RAPIDS_VERSION_MAJOR "${CMAKE_MATCH_1}")
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11 changes: 4 additions & 7 deletions cpp/include/cudf/detail/utilities/host_vector.hpp
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Expand Up @@ -53,10 +53,6 @@ class rmm_host_allocator<void> {
};
};

template <class DesiredProperty, class... Properties>
inline constexpr bool contains_property =
(cuda::std::is_same_v<DesiredProperty, Properties> || ... || false);

/*! \p rmm_host_allocator is a CUDA-specific host memory allocator
* that employs \c `cudf::host_async_resource_ref` for allocation.
*
Expand Down Expand Up @@ -102,11 +98,12 @@ class rmm_host_allocator {
#ifdef __CUDACC__
#pragma nv_exec_check_disable
#endif
template <class... Properties>
rmm_host_allocator(async_host_resource_ref<Properties...> _mr, rmm::cuda_stream_view _stream)
template <typename ResourceType>
rmm_host_allocator(ResourceType _mr, rmm::cuda_stream_view _stream)
: mr(_mr),
stream(_stream),
_is_device_accessible{contains_property<cuda::mr::device_accessible, Properties...>}
_is_device_accessible{
cuda::mr::synchronous_resource_with<ResourceType, cuda::mr::device_accessible>}
{
}

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5 changes: 3 additions & 2 deletions cpp/src/quantiles/tdigest/tdigest_aggregation.cu
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Expand Up @@ -738,8 +738,9 @@ cluster_info generate_group_cluster_info(int delta,
// CPU. This specifically addresses customer use cases with large inputs and small numbers of
// groups, such as just 1. if we're going to be using the CPU, use pinned for a few of the temp
// buffers
auto temp_mr =
use_cpu ? cudf::get_pinned_memory_resource() : cudf::get_current_device_resource_ref();
rmm::device_async_resource_ref temp_mr =
use_cpu ? rmm::device_async_resource_ref{cudf::get_pinned_memory_resource()}
: cudf::get_current_device_resource_ref();

// output from the function
cluster_info cinfo;
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