56fd68e7dd
CCCL (CUDA C++ Core Libraries) provides: - CUB: device/block/warp-level GPU primitives (reduce, scan, sort, topk) - Thrust: high-level parallel algorithms (transform_reduce, sort, scan) - libcudacxx: CUDA C++ standard library (atomics, barriers, memory) - cudax: experimental features (memory resources, allocators) - Tuning policies: per-SM hardware-specific algorithm parameters Competition optimization vectors mapped to CCCL: - Output TPS (83% weight): warp_reduce, block_reduce, device_topk - Input TPS (14% weight): device_scan, block_load, prefetch - Cache TPS (3% weight): prefix caching strategy patterns - Memory (0.9 util): pooled/cached/buddy allocators Source: https://github.com/NVIDIA/cccl (shallow clone, HEAD only) License: Apache-2.0
30 lines
996 B
CMake
30 lines
996 B
CMake
foreach (thrust_target IN LISTS THRUST_TARGETS)
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thrust_get_target_property(config_device ${thrust_target} DEVICE)
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thrust_get_target_property(config_prefix ${thrust_target} PREFIX)
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set(framework_target ${config_prefix}.test.framework)
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if ("CUDA" STREQUAL "${config_device}")
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set(
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framework_srcs #
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testframework.cu
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cuda/testframework.cu
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)
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else()
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# Wrap the cu file inside a .cpp file for non-CUDA builds
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thrust_wrap_cu_in_cpp(framework_srcs testframework.cu ${thrust_target})
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endif()
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add_library(${framework_target} STATIC ${framework_srcs})
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cccl_configure_target(${framework_target})
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cccl_ensure_metatargets(${framework_target})
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target_link_libraries(${framework_target} PUBLIC ${thrust_target})
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target_include_directories(
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${framework_target}
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PRIVATE "${Thrust_SOURCE_DIR}/testing"
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)
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if ("CUDA" STREQUAL "${config_device}")
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thrust_configure_cuda_target(${framework_target} RDC ${THRUST_FORCE_RDC})
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endif()
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endforeach()
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