46 lines
2.0 KiB
Bash
Executable File
46 lines
2.0 KiB
Bash
Executable File
#!/usr/bin/env bash
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# SPDX-License-Identifier: AGPL-3.0-or-later
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# Copyright (C) 2026 David (Corey) Herrera
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# build_train_gpu.sh — build the on-device GPU training driver (Phase 3, Chunk B).
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#
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# Runs on a K80 host (GPU 0), from any directory. Compiles the CPU-oracle
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# translation units with gcc-11 first (self-contained; no BLAS), then nvcc
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# device-links the driver against them. Mirrors the Phase-2/3 recipe.
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#
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# bash cuda_kernels/build_train_gpu.sh (outputs land in <repo>/build/)
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#
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# Requires data/enwik8 (exactly 100,000,000 bytes) for a run. Then e.g.:
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# CUDA_VISIBLE_DEVICES=0 build/train_gpu --opt sr4 --steps 1000
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# CUDA_VISIBLE_DEVICES=0 build/train_gpu --opt adamw --steps 1000
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set -euo pipefail
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cd "$(dirname "$0")/.."
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CUDA=${CUDA:-/usr/local/cuda-11.4}
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NVCC=$CUDA/bin/nvcc
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CC=${CC:-gcc-11}
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ARCH=sm_37
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mkdir -p build
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OBJ=build
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# CPU oracle objects (gcc-11; -O2, NO -ffast-math so the SR4 scale reduction is
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# not reassociated — keeps the GPU SR4 step bit-exact vs the reference core).
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$CC -O2 -I. -c rwkvx/rx_pretrain.c -o $OBJ/rx_pretrain_tg.o
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$CC -O2 -I. -c data/fd_byte_dataset.c -o $OBJ/fd_byte_dataset_tg.o
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$CC -O2 -I. -c ternary_optim/ternary_optim.c -o $OBJ/ternary_optim_tg.o
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# Driver (includes cuda_kernels/fullmodel.cu + cuda_kernels/optim.cu).
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# opt#3: --default-stream per-thread routes every <<<...,0>>> kernel launch (and,
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# via an explicit cublasSetStream, cuBLAS) onto the per-thread default stream,
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# which is capturable — the prerequisite for capturing the whole train step as a
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# CUDA graph. The standalone test_*_cuda builds do NOT use this flag (legacy
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# default stream), and the shared code is byte-identical either way.
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$NVCC -O2 -arch=$ARCH -ccbin $CC -Wno-deprecated-gpu-targets \
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--default-stream per-thread \
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-isystem cuda_kernels/nvcc_shim -I. \
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cuda_kernels/train_gpu.cu \
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$OBJ/rx_pretrain_tg.o $OBJ/fd_byte_dataset_tg.o $OBJ/ternary_optim_tg.o \
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-L$CUDA/lib64 -lcublas -lm -o build/train_gpu
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echo "built build/train_gpu"
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