russell@unturf.com
f11e310b24
Establishes the integration pattern for lumbda's future cuda primitive
across Python / C / asm tiers without dragging the CUDA toolchain into
lumbda's core build.
Shape: leaf binary that every tier spawns via its existing process-
spawn primitive & talks to through S-expression input + output
portals. Asm tier inherits via fork + execve syscalls; no libcudart
linkage; no DKMS dependency at lumbda build time.
Files:
shake256-fanout.cu self-contained CUDA SHAKE256 fan-out, Keccak
permutation derived from FIPS 202 reference
(tiny-sha3 lineage, CC0 → re-licensed AGPLv3)
Makefile nvcc build + make test + make bench
test_roundtrip.py validates output byte-identical to
hashlib.shake_256
bench.py device vs host throughput at N = 1k / 10k / 100k
lumbda-call.lsp reference Scheme wrapper showing the
(cuda-shake-fanout inputs out-bytes) API shape
lumbda's core would dispatch to per-tier
README.md full integration story, wire contract, the
three changes each tier needs (~20 LoC each),
generalization path for other CUDA primitives
Tested on 3090-ai (RTX 3090):
make test → PASS — 4 / 4 hashes byte-identical to hashlib.shake_256
Honest bench (32-byte inputs):
N host (Python hashlib) device (kernel launch dominated)
1,000 0.6 ms 188.1 ms
10,000 5.9 ms 195.7 ms
100,000 58.7 ms 313.8 ms
Useful primitive when inputs are larger (KB+) or N reaches millions;
honest about the launch-overhead break-even point. This is the
reference, not the win — the win is locking the API shape so each
tier registers under one stable name.
Provenance: extracted as the generic pattern from
~/git/www.foxhop.net/ecdsa/cuda/sim_gpu.cu where on-device SHAKE
delivered 2.6× memory compression for batched reversible-circuit
simulation. Re-shipping the primitive back to the lumbda repo so the
ecosystem inherits the work.
39 lines
1.5 KiB
Makefile
39 lines
1.5 KiB
Makefile
# shake256-fanout — Makefile.
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#
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# Builds the reference cuda fan-out worker. Each lumbda tier (Python,
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# C, asm) spawns this binary via its existing process-spawn primitive
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# & talks to it through input + output portal files. No tier links
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# against libcudart directly — the CUDA toolchain dependency stays
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# isolated to this directory.
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#
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# Build:
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# make all — compile shake256-fanout (needs nvcc)
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# make test — round-trip test (host + device produce identical
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# SHAKE256 outputs over a small synthetic input set)
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# make bench — bench device vs host throughput at N = 100k
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NVCC ?= nvcc
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NVCCFLAGS ?= -O3 -arch=sm_86 -Xcompiler="-O3 -Wall -Wextra"
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NVCC_PATH ?= $(shell which nvcc 2>/dev/null || echo /usr/local/cuda/bin/nvcc)
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all: shake256-fanout
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shake256-fanout: shake256-fanout.cu
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$(NVCC) $(NVCCFLAGS) -o $@ $<
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# round-trip: feed (cuda-shake-fanout (output-bytes 32) (inputs ...))
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# through the binary, compare against an external SHAKE256 reference
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# (Python hashlib.shake_256).
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test: shake256-fanout test_roundtrip.py
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@printf '(cuda-shake-fanout\n (output-bytes 32)\n (inputs\n' > /tmp/cf-in.portal
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@printf ' "00"\n "01"\n "deadbeef"\n "%s"\n' \
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"$$(python3 -c 'print("ab" * 100)')" >> /tmp/cf-in.portal
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@printf '))\n' >> /tmp/cf-in.portal
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./shake256-fanout /tmp/cf-in.portal /tmp/cf-out.portal
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python3 test_roundtrip.py /tmp/cf-in.portal /tmp/cf-out.portal
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bench: shake256-fanout bench.py
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python3 bench.py ./shake256-fanout
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clean:
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rm -f shake256-fanout /tmp/cf-in.portal /tmp/cf-out.portal
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