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…mory Introduce a dry-run execution framework that replaces device and host memory resources with lightweight fake allocators to measure peak memory usage without holding real memory. New files: - dry_run_memory_resource.hpp: dry_run_allocator (lock-free bump allocator), dry_run_device_memory_resource, dry_run_host_memory_resource, dry_run_resource_manager (RAII), and dry_run_execute() helper. - dry_run_flag.hpp: boolean dry-run flag as a raft resource, allowing algorithms to skip kernel execution during profiling. - tests/util/dry_run_memory_resource.cpp: unit tests. The dry_run_allocator probes the upstream once to obtain a base address, then atomically bumps a pointer for each allocation — no mutex, no map, no real memory held after the initial probe.
…pinned_memory_resource Add pinned and managed resources to the raft::resources handle to make it possible to customize / temporarily replace these resources
…aking change due to transitive includes in downstream libraries
Merges Remove deprecated headers (rapidsai#2939). Conflict resolutions: - rsvd.cuh: Use new mdspan-based raft::matrix::sqrt and reciprocal APIs (they have internal dry-run guards); kept cudaMemsetAsync guard - svd.cuh: Use raft::matrix::weighted_sqrt (has internal dry-run guard) - matrix.cuh: Accept deletion (deprecated, removed in main) Co-authored-by: Cursor <cursoragent@cursor.com>
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A non-breaking src-only changes to modernize the use of raft primitives across cuVS source code. The general rule applied here is to prefer raft helpers taking `raft::resources` as an argument over other raft helpers over third-party libraries. - thrust::fill / thrust::fill_n → raft::matrix::fill - thrust::transform → raft::linalg::map - thrust::sequence / thrust::tabulate → raft::linalg::map_offset - raft::linalg::unaryOp / raft::linalg::binaryOp → raft::linalg::map - raft::linalg::add (pointer-based) → raft::linalg::add (mdspan-based) - raft::copy (pointer-based) → raft::copy (mdspan-based) - raft::update_device / raft::update_host → raft::copy (mdspan-based) - raft::linalg::rowNorm → raft::linalg::norm - raft::linalg::reduce (pointer-based) → raft::linalg::reduce (mdspan-based) - cudaMemsetAsync → raft::matrix::fill The purpose of this PR is to improve the consistency in using the library code (even though sometimes at the cost of a bit more auxiliary code). This is also a prerequisite to achieving dry run compliance in cuVS if we choose to merge that in rapidsai/raft#2961 Authors: - Artem M. Chirkin (https://github.com/achirkin) Approvers: - Dante Gama Dessavre (https://github.com/dantegd) URL: rapidsai#1837
…aw CCCL references
…urrent_device_resource()
Adapt the dry-run protocol to use the unified cuda::mr resource infrastructure from fea-unify-memory-resources. Key changes: - Replace dry_run_device_memory_resource (rmm subclass) and dry_run_host_memory_resource (std::pmr subclass) with a single dry_run_resource<Upstream> template using cuda::forward_property, modeled after raft::mr::statistics_adaptor. - Replace dry_run_resource_manager (which modified the passed-in resources handle) with dry_run_resources, a standalone class that copies the resources object and provides implicit conversion to const resources&, enabling composability with other resource wrappers. - dry_run_allocator uses probe-once semantics: a single real allocation from the upstream is kept alive for the allocator's lifetime, and all subsequent allocations return the same valid pointer. - Remove obsolete pmr/pinned_memory_resource.hpp (superseded by cuda::mr::legacy_pinned_memory_resource in the unified branch). - Adapt tests to use unified resource APIs (host_resource_ref, host_device_resource_ref, get_default_host_resource, etc.). Made-with: Cursor
…ep/restore the state of resources
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The smaller diff without #2968 is viewable here: achirkin#4 |
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The dry run protocol defines a mechanism to simulate the execution of algorithms to get a precise estimate of the memory requirements for a real execution with the same parameters.
This PR:
raft::util::dry_run_execute, tracking memory resource,resource::get_dry_run_flag) that lets callers estimate peak memory usage of any RAFT algorithm without executing GPU work.Depends on (and includes all changes of) #2968