[INFRA] Import NVIDIA/CCCL upstream as optimization reference library

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

cccl_upstream/c/parallel.v2/src/binary_search.cu

@@ -0,0 +1,180 @@
+//===----------------------------------------------------------------------===//
+//
+// Part of CUDA Experimental in CUDA C++ Core Libraries,
+// under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+// SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION.
+//
+//===----------------------------------------------------------------------===//
+
+#include <cuda/std/version>
+
+#include <cstdio>
+#include <cstring>
+#include <memory>
+
+#include <cccl/c/binary_search.h>
+#include <hostjit/codegen/cub_call.hpp>
+#include <util/build_utils.h>
+#include <util/first_call_gate.h>
+
+using namespace hostjit::codegen;
+
+// (d_in_0, num_items, d_in_1, num_values, d_out_0, op_0_state, stream)
+using binary_search_fn_t = int (*)(void*, unsigned long long, void*, unsigned long long, void*, void*, void*);
+
+CUresult cccl_device_binary_search_build_ex(
+  cccl_device_binary_search_build_result_t* build_ptr,
+  cccl_binary_search_mode_t mode,
+  cccl_iterator_t d_data,
+  cccl_iterator_t d_values,
+  cccl_iterator_t d_out,
+  cccl_op_t op,
+  int cc_major,
+  int cc_minor,
+  const char* cub_path,
+  const char* thrust_path,
+  const char* libcudacxx_path,
+  const char* ctk_path,
+  cccl_build_config* config)
+try
+{
+  if (build_ptr == nullptr)
+  {
+    return CUDA_ERROR_INVALID_VALUE;
+  }
+#if CCCL_OS(WINDOWS)
+  build_ptr->first_call_state = nullptr;
+#endif
+  const std::string cccl_include_str  = cccl::detail::parse_cccl_include_path(libcudacxx_path);
+  const std::string ctk_root_str      = cccl::detail::parse_ctk_root(ctk_path);
+  const char* const cccl_include_path = cccl_include_str.empty() ? nullptr : cccl_include_str.c_str();
+  const char* const ctk_root          = ctk_root_str.empty() ? nullptr : ctk_root_str.c_str();
+  cccl::detail::MergedBuildConfig merged(config, cub_path, thrust_path);
+#if CCCL_OS(WINDOWS)
+  auto first_call_state = std::make_unique<cccl::detail::first_call_gate>();
+#endif
+
+  const char* find_fn =
+    (mode == CCCL_BINARY_SEARCH_LOWER_BOUND) ? "cub::DeviceFind::LowerBound" : "cub::DeviceFind::UpperBound";
+
+  // env_stream uses the env-based DeviceFind overload so CUB manages its own
+  // temp storage via the env's memory_resource — no caller-managed buffer.
+  auto result =
+    CubCall::from("cub/device/device_find.cuh")
+      .run(find_fn)
+      .name("cccl_jit_binary_search")
+      .with(in(d_data), num_haystack, in(d_values), num_needles, out(d_out), cmp(op), env_stream)
+      .compile(cc_major, cc_minor, merged.get(), ctk_root, cccl_include_path);
+
+  build_ptr->cc = cc_major * 10 + cc_minor;
+  cccl::detail::copy_cubin(result.cubin, build_ptr->payload, build_ptr->payload_size);
+  build_ptr->jit_compiler = result.compiler;
+#if CCCL_OS(WINDOWS)
+  build_ptr->first_call_state = first_call_state.release();
+#endif
+  build_ptr->binary_search_fn = result.fn_ptr;
+
+  return CUDA_SUCCESS;
+}
+catch (const std::exception& exc)
+{
+  fprintf(stderr, "\nEXCEPTION in cccl_device_binary_search_build_ex(): %s\n", exc.what());
+  return CUDA_ERROR_UNKNOWN;
+}
+
+CUresult cccl_device_binary_search(
+  cccl_device_binary_search_build_result_t build,
+  cccl_iterator_t d_data,
+  uint64_t num_items,
+  cccl_iterator_t d_values,
+  uint64_t num_values,
+  cccl_iterator_t d_out,
+  cccl_op_t op,
+  CUstream stream)
+try
+{
+  if (!build.binary_search_fn)
+  {
+    return CUDA_ERROR_INVALID_VALUE;
+  }
+  const auto fn = reinterpret_cast<binary_search_fn_t>(build.binary_search_fn);
+
+#if CCCL_OS(WINDOWS)
+  if (!build.first_call_state)
+  {
+    return CUDA_ERROR_INVALID_VALUE;
+  }
+  const auto invoke = [&] {
+    return fn(
+      d_data.state, num_items, d_values.state, num_values, d_out.state, op.state, reinterpret_cast<void*>(stream));
+  };
+  // Empty calls return before DeviceTransform initializes its static launch configuration,
+  // so they must not complete the first-call gate.
+  const int status =
+    num_values == 0 ? invoke() : static_cast<cccl::detail::first_call_gate*>(build.first_call_state)->invoke(invoke);
+#else
+  const int status =
+    fn(d_data.state, num_items, d_values.state, num_values, d_out.state, op.state, reinterpret_cast<void*>(stream));
+#endif
+  return (status == 0) ? CUDA_SUCCESS : CUDA_ERROR_UNKNOWN;
+}
+catch (const std::exception& exc)
+{
+  fprintf(stderr, "\nEXCEPTION in cccl_device_binary_search(): %s\n", exc.what());
+  return CUDA_ERROR_UNKNOWN;
+}
+
+CUresult cccl_device_binary_search_build(
+  cccl_device_binary_search_build_result_t* build,
+  cccl_binary_search_mode_t mode,
+  cccl_iterator_t d_data,
+  cccl_iterator_t d_values,
+  cccl_iterator_t d_out,
+  cccl_op_t op,
+  int cc_major,
+  int cc_minor,
+  const char* cub_path,
+  const char* thrust_path,
+  const char* libcudacxx_path,
+  const char* ctk_path)
+{
+  return cccl_device_binary_search_build_ex(
+    build,
+    mode,
+    d_data,
+    d_values,
+    d_out,
+    op,
+    cc_major,
+    cc_minor,
+    cub_path,
+    thrust_path,
+    libcudacxx_path,
+    ctk_path,
+    nullptr);
+}
+
+CUresult cccl_device_binary_search_cleanup(cccl_device_binary_search_build_result_t* build_ptr)
+try
+{
+  if (build_ptr == nullptr)
+  {
+    return CUDA_ERROR_INVALID_VALUE;
+  }
+
+#if CCCL_OS(WINDOWS)
+  delete static_cast<cccl::detail::first_call_gate*>(build_ptr->first_call_state);
+  build_ptr->first_call_state = nullptr;
+#endif
+  cccl::detail::release_jit_artifacts(build_ptr);
+  build_ptr->binary_search_fn = nullptr;
+
+  return CUDA_SUCCESS;
+}
+catch (const std::exception& exc)
+{
+  fprintf(stderr, "\nEXCEPTION in cccl_device_binary_search_cleanup(): %s\n", exc.what());
+  return CUDA_ERROR_UNKNOWN;
+}