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Revert D94939843: Upgrade cuVS Version to 26.02, switch various BUCK files over to 26.02

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Differential Revision:
D94939843

Original commit changeset: 05a287aaaaa9

Original Phabricator Diff: D94939843

fbshipit-source-id: 4207d5d7b37d644a8e8d2d1c1ad9b26723e07d73
This commit is contained in:
Akshay Mahesh
2026-03-17 02:38:50 -07:00
committed by meta-codesync[bot]
parent 55a47c927c
commit c24598a4c4
16 changed files with 72 additions and 145 deletions
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.github/actions/build_cmake/action.yml
+2 -2
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@@ -74,7 +74,7 @@ runs:
conda install -y -q cuda-toolkit=12.6 gxx_linux-64=12.4 -c "nvidia/label/cuda-12.6"
# and CUDA from cuVS channel for cuVS builds
elif [ "${{ inputs.cuvs }}" = "ON" ]; then
conda install -y -q libcuvs=26.02 'cuda-version=12.9' cuda-toolkit=12.9 sysroot_linux-64=2.34 -c rapidsai -c rapidsai-nightly -c conda-forge
conda install -y -q libcuvs=25.10 'cuda-version=12.6' cuda-toolkit=12.6 gxx_linux-64=13.4.0 -c rapidsai -c rapidsai-nightly -c conda-forge
fi
# install SVS runtime for SVS builds
@@ -87,7 +87,7 @@ runs:
: # skip torch install via conda, we need to install via pip to get
# ROCm-enabled version until it's supported in conda by PyTorch
elif [ "${{ inputs.gpu }}" = "ON" ]; then
conda install -y -q "pytorch>=2.7" "pytorch-gpu>=2.7" -c pytorch -c "nvidia/label/12.9"
conda install -y -q "pytorch>=2.7" "pytorch-gpu>=2.7" -c pytorch -c "nvidia/label/12.6"
else
# TestLowLevelIVF.IVFRQ hangs on pytorch>=2.7, so left it as <2.5 for now.
conda install -y -q "pytorch<2.5" -c pytorch
INSTALL.md
+4 -4
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@@ -6,7 +6,7 @@ pre-release nightly builds.
- The CPU-only faiss-cpu conda package is currently available on Linux (x86-64 and aarch64), OSX (arm64 only), and Windows (x86-64)
- faiss-gpu, containing both CPU and GPU indices, is available on Linux (x86-64 only) for CUDA 11.4 and 12.1
- faiss-gpu-cuvs package containing GPU indices provided by [NVIDIA cuVS](https://github.com/rapidsai/cuvs/) version 26.02, is available on Linux (x86-64 only) for CUDA 12.4.
- faiss-gpu-cuvs package containing GPU indices provided by [NVIDIA cuVS](https://github.com/rapidsai/cuvs/) version 25.10, is available on Linux (x86-64 only) for CUDA 12.4.
To install the latest stable release:
@@ -72,7 +72,7 @@ The optional requirements are:
- for AMD GPUs:
- AMD ROCm,
- for using NVIDIA cuVS implementations:
- libcuvs=26.02
- libcuvs=25.10
- for the python bindings:
- python 3,
- numpy,
@@ -87,9 +87,9 @@ section of the wiki](https://github.com/facebookresearch/faiss/wiki/Troubleshoot
The libcuvs dependency should be installed via conda:
```
conda install -c rapidsai -c conda-forge -c nvidia libcuvs=26.02 'cuda-version=12.6'
conda install -c rapidsai -c conda-forge -c nvidia libcuvs=25.10 'cuda-version=12.6'
```
For more ways to install cuVS 26.02, refer to the [RAPIDS Installation Guide](https://docs.rapids.ai/install).
For more ways to install cuVS 25.10, refer to the [RAPIDS Installation Guide](https://docs.rapids.ai/install).
### Building with Intel(R) SVS
cmake/thirdparty/fetch_rapids.cmake
Vendored
+2 -2
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@@ -15,11 +15,11 @@
# or implied. See the License for the specific language governing permissions and limitations under
# the License.
# =============================================================================
set(RAPIDS_VERSION "26.02")
set(RAPIDS_VERSION "25.10")
set(rapids-cmake-version ${RAPIDS_VERSION})
if(NOT EXISTS ${CMAKE_CURRENT_BINARY_DIR}/FAISS_RAPIDS.cmake)
file(DOWNLOAD https://raw.githubusercontent.com/rapidsai/rapids-cmake/release/${RAPIDS_VERSION}/RAPIDS.cmake
file(DOWNLOAD https://raw.githubusercontent.com/rapidsai/rapids-cmake/branch-${RAPIDS_VERSION}/RAPIDS.cmake
${CMAKE_CURRENT_BINARY_DIR}/FAISS_RAPIDS.cmake)
endif()
include(${CMAKE_CURRENT_BINARY_DIR}/FAISS_RAPIDS.cmake)
conda/faiss-gpu-cuvs/meta.yaml
+8 -8
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@@ -6,9 +6,9 @@
{% set version = environ.get('GIT_DESCRIBE_TAG').lstrip('v') %}
{% set suffix = "_nightly" if environ.get('PACKAGE_TYPE') == 'nightly' else "" %}
{% set number = GIT_DESCRIBE_NUMBER %}
{% set cuda_constraints=">=12.9,<13.0" %}
{% set libcublas_constraints=">=12.9,<13.0" %}
{% set cudart_constraints=">=12.9,<13.0" %}
{% set cuda_constraints=">=12.6,<12.7" %}
{% set libcublas_constraints=">=12.6,<12.7" %}
{% set cudart_constraints=">=12.6,<12.7" %}
package:
name: faiss-pkg
@@ -60,7 +60,7 @@ outputs:
- _openmp_mutex =4.5=2_kmp_llvm # [x86_64]
- mkl >=2024.2.2 # [x86_64]
- openblas =0.3.30 # [not x86_64]
- libcuvs =26.02
- libcuvs =25.10
- cuda-version {{ cuda_constraints }}
- libsvs-runtime =0.2.0 # [x86_64 and linux]
run:
@@ -69,7 +69,7 @@ outputs:
- openblas =0.3.30 # [not x86_64]
- cuda-cudart {{ cuda_constraints }}
- libcublas {{ libcublas_constraints }}
- libcuvs =26.02
- libcuvs =25.10
- cuda-version {{ cuda_constraints }}
- libnvjitlink
- libsvs-runtime =0.2.0 # [x86_64 and linux]
@@ -91,10 +91,10 @@ outputs:
string: "py{{ PY_VER }}_h{{ PKG_HASH }}_{{ number }}_cuda{{ cudatoolkit }}{{ suffix }}"
requirements:
build:
- {{ compiler('cxx') }} =14.2
- sysroot_linux-64 =2.34 # [linux64]
- {{ compiler('cxx') }} =12.4
- sysroot_linux-64 =2.17 # [linux64]
- swig =4.0
- cmake >=3.30.4
- cmake >=3.26.4
- make =4.2 # [not win]
- _openmp_mutex =4.5=2_kmp_llvm # [x86_64]
- mkl >=2024.2.2 # [x86_64]
faiss/gpu/GpuDistance.cu
+1 -1
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@@ -238,7 +238,7 @@ void bfKnn(GpuResourcesProvider* prov, const GpuDistanceParams& args) {
if (should_use_cuvs(args) && args.queriesRowMajor == args.vectorsRowMajor &&
args.outIndicesType == IndicesDataType::I64 &&
args.vectorType == DistanceDataType::F32 && args.k > 0) {
auto distance = metricFaissToCuvs(args.metric, false);
cuvsDistanceType distance = metricFaissToCuvs(args.metric, false);
auto resImpl = prov->getResources();
auto res = resImpl.get();
faiss/gpu/GpuIndexCagra.h
+5 -5
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@@ -193,14 +193,14 @@ struct GpuIndexCagraConfig : public GpuIndexConfig {
enum class search_algo {
/// For large batch sizes.
SINGLE_CTA = 0,
SINGLE_CTA,
/// For small batch sizes.
MULTI_CTA = 1,
MULTI_KERNEL = 2,
AUTO = 100
MULTI_CTA,
MULTI_KERNEL,
AUTO
};
enum class hash_mode { HASH = 0, SMALL = 1, AUTO = 100 };
enum class hash_mode { HASH, SMALL, AUTO };
struct SearchParametersCagra : SearchParameters {
/// Maximum number of queries to search at the same time (batch size). Auto
faiss/gpu/GpuResources.h
+1 -1
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@@ -33,7 +33,7 @@
#if defined USE_NVIDIA_CUVS
#include <raft/core/device_resources.hpp>
#include <rmm/mr/device_memory_resource.hpp>
#include <rmm/mr/device/device_memory_resource.hpp>
#endif
namespace faiss {
faiss/gpu/StandardGpuResources.cpp
+9 -9
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@@ -23,9 +23,9 @@
#if defined USE_NVIDIA_CUVS
#include <raft/core/device_resources.hpp>
#include <rmm/mr/managed_memory_resource.hpp>
#include <rmm/mr/per_device_resource.hpp>
#include <rmm/mr/pinned_host_memory_resource.hpp>
#include <rmm/mr/device/managed_memory_resource.hpp>
#include <rmm/mr/device/per_device_resource.hpp>
#include <rmm/mr/host/pinned_memory_resource.hpp>
#include <memory>
#endif
@@ -93,7 +93,7 @@ StandardGpuResourcesImpl::StandardGpuResourcesImpl()
:
#if defined USE_NVIDIA_CUVS
mmr_(new rmm::mr::managed_memory_resource),
pmr_(new rmm::mr::pinned_host_memory_resource),
pmr_(new rmm::mr::pinned_memory_resource),
#endif
pinnedMemAlloc_(nullptr),
pinnedMemAllocSize_(0),
@@ -164,7 +164,7 @@ StandardGpuResourcesImpl::~StandardGpuResourcesImpl() {
if (pinnedMemAlloc_) {
#if defined USE_NVIDIA_CUVS
pmr_->deallocate_sync(pinnedMemAlloc_, pinnedMemAllocSize_);
pmr_->deallocate(pinnedMemAlloc_, pinnedMemAllocSize_);
#else
auto err = cudaFreeHost(pinnedMemAlloc_);
FAISS_ASSERT_FMT(
@@ -350,7 +350,7 @@ void StandardGpuResourcesImpl::initializeForDevice(int device) {
// pinned memory allocation
if (defaultStreams_.empty() && pinnedMemSize_ > 0) {
try {
pinnedMemAlloc_ = pmr_->allocate_sync(pinnedMemSize_);
pinnedMemAlloc_ = pmr_->allocate(pinnedMemSize_);
} catch (const std::bad_alloc& rmm_ex) {
FAISS_THROW_MSG("CUDA memory allocation error");
}
@@ -549,7 +549,7 @@ void* StandardGpuResourcesImpl::allocMemory(const AllocRequest& req) {
rmm::mr::device_memory_resource* current_mr =
rmm::mr::get_per_device_resource(
rmm::cuda_device_id{adjReq.device});
p = current_mr->allocate(adjReq.stream, adjReq.size);
p = current_mr->allocate_async(adjReq.size, adjReq.stream);
adjReq.mr = current_mr;
} catch (const std::bad_alloc& rmm_ex) {
FAISS_THROW_MSG("CUDA memory allocation error");
@@ -584,7 +584,7 @@ void* StandardGpuResourcesImpl::allocMemory(const AllocRequest& req) {
// TODO: change this to use the current device resource once RMM has
// a way to retrieve a "guaranteed" managed memory resource for a
// device.
p = mmr_->allocate(adjReq.stream, adjReq.size);
p = mmr_->allocate_async(adjReq.size, adjReq.stream);
adjReq.mr = mmr_.get();
} catch (const std::bad_alloc& rmm_ex) {
FAISS_THROW_MSG("CUDA memory allocation error");
@@ -648,7 +648,7 @@ void StandardGpuResourcesImpl::deallocMemory(int device, void* p) {
req.space == MemorySpace::Device ||
req.space == MemorySpace::Unified) {
#if defined USE_NVIDIA_CUVS
req.mr->deallocate(req.stream, p, req.size);
req.mr->deallocate_async(p, req.size, req.stream);
#else
auto err = cudaFree(p);
FAISS_ASSERT_FMT(
faiss/gpu/StandardGpuResources.h
+3 -4
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@@ -25,8 +25,7 @@
#if defined USE_NVIDIA_CUVS
#include <raft/core/device_resources.hpp>
#include <rmm/mr/device_memory_resource.hpp>
#include <rmm/mr/pinned_host_memory_resource.hpp>
#include <rmm/mr/host/pinned_memory_resource.hpp>
#endif
#include <faiss/gpu/GpuResources.h>
@@ -173,8 +172,8 @@ class StandardGpuResourcesImpl : public GpuResources {
// managed_memory_resource
std::unique_ptr<rmm::mr::device_memory_resource> mmr_;
// pinned_host_memory_resource
std::unique_ptr<rmm::mr::pinned_host_memory_resource> pmr_;
// pinned_memory_resource
std::unique_ptr<rmm::mr::host_memory_resource> pmr_;
#endif
/// Pinned memory allocation for use with this GPU
faiss/gpu/impl/BinaryCuvsCagra.cu
+2 -7
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@@ -49,9 +49,9 @@ BinaryCuvsCagra::BinaryCuvsCagra(
IndicesOptions indicesOptions)
: resources_(resources),
dim_(dim),
store_dataset_(store_dataset),
graph_build_algo_(graph_build_algo),
nn_descent_niter_(nn_descent_niter) {
nn_descent_niter_(nn_descent_niter),
store_dataset_(store_dataset) {
FAISS_THROW_IF_NOT_MSG(
indicesOptions == faiss::gpu::INDICES_64_BIT,
"only INDICES_64_BIT is supported for cuVS CAGRA index");
@@ -161,11 +161,6 @@ void BinaryCuvsCagra::train(idx_t n, const uint8_t* x) {
cuvs::neighbors::cagra::graph_build_params::iterative_search_params
graph_build_params;
index_params_.graph_build_params = graph_build_params;
if (index_params_.graph_degree ==
index_params_.intermediate_graph_degree) {
index_params_.intermediate_graph_degree =
1.5 * index_params_.graph_degree;
}
}
if (getDeviceForAddress(x) >= 0) {
faiss/gpu/impl/CuvsCagra.cuh
+2 -7
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@@ -39,14 +39,9 @@ namespace faiss {
/// Algorithm used to build underlying CAGRA graph
enum class cagra_build_algo { IVF_PQ, NN_DESCENT };
enum class cagra_search_algo {
SINGLE_CTA = 0,
MULTI_CTA = 1,
MULTI_KERNEL = 2,
AUTO = 100
};
enum class cagra_search_algo { SINGLE_CTA, MULTI_CTA };
enum class cagra_hash_mode { HASH = 0, SMALL = 1, AUTO = 100 };
enum class cagra_hash_mode { HASH, SMALL, AUTO };
namespace gpu {
faiss/gpu/impl/CuvsFlatIndex.cu
+1 -1
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@@ -91,7 +91,7 @@ void CuvsFlatIndex::query(
outDistances.getSize(0),
outDistances.getSize(1));
auto distance = metricFaissToCuvs(metric, exactDistance);
cuvsDistanceType distance = metricFaissToCuvs(metric, exactDistance);
std::optional<raft::device_vector_view<const float, int64_t>>
norms_view = raft::make_device_vector_view(
faiss/gpu/impl/CuvsIVFPQ.cu
+19 -83
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@@ -129,14 +129,8 @@ void CuvsIVFPQ::updateQuantizer(Index* quantizer) {
cuvs::neighbors::ivf_pq::helpers::reset_index(
raft_handle, cuvs_index.get());
auto mutable_rotation_matrix_view =
raft::make_device_matrix_view<float, uint32_t>(
const_cast<float*>(
cuvs_index->rotation_matrix().data_handle()),
cuvs_index->rotation_matrix().extent(0),
cuvs_index->rotation_matrix().extent(1));
cuvs::neighbors::ivf_pq::helpers::make_rotation_matrix(
raft_handle, mutable_rotation_matrix_view, false);
raft_handle, cuvs_index.get(), false);
// If the index instance is a GpuIndexFlat, then we can use direct access to
// the centroids within.
@@ -155,60 +149,22 @@ void CuvsIVFPQ::updateQuantizer(Index* quantizer) {
// as float32 and store locally
gpuData->reconstruct(0, gpuData->getSize(), centroids);
auto mutable_centers_view =
raft::make_device_matrix_view<float, uint32_t>(
const_cast<float*>(
cuvs_index->centers().data_handle()),
numLists_,
cuvs_index->centers().extent(1));
auto mutable_centers_rot_view =
raft::make_device_matrix_view<float, uint32_t>(
const_cast<float*>(
cuvs_index->centers_rot().data_handle()),
cuvs_index->centers_rot().extent(0),
cuvs_index->centers_rot().extent(1));
cuvs::neighbors::ivf_pq::helpers::pad_centers_with_norms(
cuvs::neighbors::ivf_pq::helpers::set_centers(
raft_handle,
raft::make_const_mdspan(
raft::make_device_matrix_view<float, uint32_t>(
centroids.data(), numLists_, dim_)),
mutable_centers_view);
cuvs::neighbors::ivf_pq::helpers::rotate_padded_centers(
raft_handle,
cuvs_index->centers(),
cuvs_index->rotation_matrix(),
mutable_centers_rot_view);
cuvs_index.get(),
raft::make_device_matrix_view<float, uint32_t>(
centroids.data(), numLists_, dim_));
} else {
/// No reconstruct needed since the centers are already in float32
// The FlatIndex keeps its data in float32, so we can merely
// reference it
auto centroids = gpuData->getVectorsFloat32Ref();
auto mutable_centers_view =
raft::make_device_matrix_view<float, uint32_t>(
const_cast<float*>(
cuvs_index->centers().data_handle()),
numLists_,
cuvs_index->centers().extent(1));
auto mutable_centers_rot_view =
raft::make_device_matrix_view<float, uint32_t>(
const_cast<float*>(
cuvs_index->centers_rot().data_handle()),
cuvs_index->centers_rot().extent(0),
cuvs_index->centers_rot().extent(1));
cuvs::neighbors::ivf_pq::helpers::pad_centers_with_norms(
cuvs::neighbors::ivf_pq::helpers::set_centers(
raft_handle,
raft::make_const_mdspan(
raft::make_device_matrix_view<float, uint32_t>(
centroids.data(), numLists_, dim_)),
mutable_centers_view);
cuvs::neighbors::ivf_pq::helpers::rotate_padded_centers(
raft_handle,
cuvs_index->centers(),
cuvs_index->rotation_matrix(),
mutable_centers_rot_view);
cuvs_index.get(),
raft::make_device_matrix_view<float, uint32_t>(
centroids.data(), numLists_, dim_));
}
} else {
DeviceTensor<float, 2, true> centroids(
@@ -224,30 +180,11 @@ void CuvsIVFPQ::updateQuantizer(Index* quantizer) {
centroids.copyFrom(vecs, stream);
// Create mutable views for output parameters
auto mutable_centers_view =
raft::make_device_matrix_view<float, uint32_t>(
const_cast<float*>(cuvs_index->centers().data_handle()),
numLists_,
cuvs_index->centers().extent(1));
auto mutable_centers_rot_view =
raft::make_device_matrix_view<float, uint32_t>(
const_cast<float*>(
cuvs_index->centers_rot().data_handle()),
cuvs_index->centers_rot().extent(0),
cuvs_index->centers_rot().extent(1));
cuvs::neighbors::ivf_pq::helpers::pad_centers_with_norms(
cuvs::neighbors::ivf_pq::helpers::set_centers(
raft_handle,
raft::make_const_mdspan(
raft::make_device_matrix_view<float, uint32_t>(
centroids.data(), numLists_, dim_)),
mutable_centers_view);
cuvs::neighbors::ivf_pq::helpers::rotate_padded_centers(
raft_handle,
cuvs_index->centers(),
cuvs_index->rotation_matrix(),
mutable_centers_rot_view);
cuvs_index.get(),
raft::make_device_matrix_view<float, uint32_t>(
centroids.data(), numLists_, dim_));
}
setPQCentroids_();
@@ -467,11 +404,10 @@ void CuvsIVFPQ::copyInvertedListsFrom(const InvertedLists* ivf) {
auto& cuvs_index_lists = cuvs_index->lists();
// conservative memory alloc for cloning cpu inverted lists
cuvs::neighbors::ivf_pq::list_spec_interleaved<uint32_t, idx_t>
ivf_list_spec{
static_cast<uint32_t>(bitsPerSubQuantizer_),
static_cast<uint32_t>(numSubQuantizers_),
true};
cuvs::neighbors::ivf_pq::list_spec<uint32_t, idx_t> ivf_list_spec{
static_cast<uint32_t>(bitsPerSubQuantizer_),
static_cast<uint32_t>(numSubQuantizers_),
true};
for (size_t i = 0; i < nlist; ++i) {
size_t listSize = ivf->list_size(i);
@@ -490,7 +426,7 @@ void CuvsIVFPQ::copyInvertedListsFrom(const InvertedLists* ivf) {
// This cuVS list must currently be empty
FAISS_ASSERT(getListLength(i) == 0);
cuvs::neighbors::ivf_pq::helpers::resize_list(
cuvs::neighbors::ivf::resize_list(
raft_handle,
cuvs_index_lists[i],
ivf_list_spec,
@@ -584,7 +520,7 @@ void CuvsIVFPQ::setPQCentroids_() {
auto stream = resources_->getDefaultStreamCurrentDevice();
raft::copy(
const_cast<float*>(cuvs_index->pq_centers().data_handle()),
cuvs_index->pq_centers().data_handle(),
pqCentroidsInnermostCode_.data(),
pqCentroidsInnermostCode_.numElements(),
stream);
faiss/gpu/utils/CuvsUtils.cu
-1
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@@ -31,7 +31,6 @@
#include <thrust/copy.h>
#include <thrust/gather.h>
#include <thrust/iterator/counting_iterator.h>
#include <thrust/reduce.h>
namespace faiss {
faiss/gpu/utils/CuvsUtils.h
+10 -10
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@@ -27,32 +27,32 @@
#include <faiss/gpu/GpuResources.h>
#include <faiss/gpu/utils/Tensor.cuh>
#include <cuvs/distance/distance.hpp>
#include <cuvs/distance/distance.h>
#pragma GCC visibility push(default)
namespace faiss {
namespace gpu {
inline cuvs::distance::DistanceType metricFaissToCuvs(
inline cuvsDistanceType metricFaissToCuvs(
MetricType metric,
bool exactDistance) {
switch (metric) {
case MetricType::METRIC_INNER_PRODUCT:
return cuvs::distance::DistanceType::InnerProduct;
return cuvsDistanceType::InnerProduct;
case MetricType::METRIC_L2:
return cuvs::distance::DistanceType::L2Expanded;
return cuvsDistanceType::L2Expanded;
case MetricType::METRIC_L1:
return cuvs::distance::DistanceType::L1;
return cuvsDistanceType::L1;
case MetricType::METRIC_Linf:
return cuvs::distance::DistanceType::Linf;
return cuvsDistanceType::Linf;
case MetricType::METRIC_Lp:
return cuvs::distance::DistanceType::LpUnexpanded;
return cuvsDistanceType::LpUnexpanded;
case MetricType::METRIC_Canberra:
return cuvs::distance::DistanceType::Canberra;
return cuvsDistanceType::Canberra;
case MetricType::METRIC_BrayCurtis:
return cuvs::distance::DistanceType::BrayCurtis;
return cuvsDistanceType::BrayCurtis;
case MetricType::METRIC_JensenShannon:
return cuvs::distance::DistanceType::JensenShannon;
return cuvsDistanceType::JensenShannon;
default:
RAFT_FAIL("Distance type not supported");
}
faiss/python/CMakeLists.txt
+3
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@@ -230,6 +230,9 @@ if(FAISS_ENABLE_GPU)
target_link_libraries(faiss_example_external_module PRIVATE hip::host)
else()
find_package(CUDAToolkit REQUIRED)
if(FAISS_ENABLE_CUVS)
find_package(cuvs)
endif()
target_link_libraries(swigfaiss PRIVATE CUDA::cudart $<$<BOOL:${FAISS_ENABLE_CUVS}>:cuvs::cuvs>)
target_link_libraries(swigfaiss_avx2 PRIVATE CUDA::cudart $<$<BOOL:${FAISS_ENABLE_CUVS}>:cuvs::cuvs>)
target_link_libraries(swigfaiss_avx512 PRIVATE CUDA::cudart $<$<BOOL:${FAISS_ENABLE_CUVS}>:cuvs::cuvs>)