[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/benchmarks/scripts/submit_benchmark_job.sh

@@ -0,0 +1,47 @@
+#!/usr/bin/env bash
+
+# This script schedules a SLURM job via crun on computelab to run all CCCL benchmarks and produce a benchmark database
+# TODO: set those accordingly
+scratch=/home/scratch."$USER"_sw
+node_selector="cpu.arch=x86_64 and gpu.product_name='*B200*'"
+container_image="rapidsai/devcontainers:26.06-cpp-gcc14-cuda13.2"
+jobtime="4:00:00"
+benchmark_preset="benchmark"
+
+batch_script=$scratch/batch.sh
+cat << BATCH_SCRIPT > "$batch_script"
+#!/usr/bin/env bash
+
+pip install --break-system-packages fpzip pandas scipy
+
+# clone CCCL
+host=\$(hostname)
+cd $scratch
+if [ -d "\$host/cccl" ]; then
+    rm -r \$host/cccl
+fi
+mkdir \$host
+cd \$host
+git clone --depth 1 git@github.com:NVIDIA/cccl.git
+cd cccl
+
+# configure cmake
+mkdir build_perf
+cd build_perf
+cmake .. --preset $benchmark_preset
+
+# run benchmarks
+export CUDA_VISIBLE_DEVICES=0
+export PYTHONPATH=../benchmarks/scripts/
+../benchmarks/scripts/run.py
+
+echo "Benchmark done. Results in $scratch/\$host/cccl/build_perf/cccl_meta_bench.db"
+BATCH_SCRIPT
+chmod +x "$batch_script"
+
+# schedule SLURM job
+echo "Scheduling script $batch_script"
+echo "#################################################################################"
+cat "$batch_script"
+echo "#################################################################################"
+crun -q "$node_selector" -ex -t "$jobtime" -img "$container_image" -b "$batch_script"