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Forked from upstream concrete (BSD-3-Clause-Clear, © 2024 ZAMA) at HEAD
ecb729bb. Modifications copyright © 2026 Lux Industries Inc.
Rebranding scope:
- Python module concrete → torus (across frontends/torus-python)
- Rust module concrete-* → torus-* (across frontends/torus-rust)
- MLIR dialect concretelang → toruslang (across compilers/torus-compiler)
- Compiler optimizer concrete-optimizer → torus-optimizer
- Backend concrete-cpu / concrete-cuda → torus-cpu / torus-cuda
- Wire protocol concrete-protocol → torus-protocol
- Parameter-curves concrete-security-curves-* → torus-security-curves-*
- Public symbols concretelib → toruslib, ConcreteLang → TorusLang
- URLs github.com/zama-ai/concrete → github.com/luxfhe/torus
- URLs docs.zama.ai/concrete → docs.luxfhe.com/torus
Legal compliance:
- LICENSE.txt retains original Copyright © 2024 ZAMA verbatim (§1-§2)
- LICENSE.txt adds modifications copyright © 2026 Lux Industries Inc.
- §3 endorsement clause: Torus is marketed exclusively as a Lux product;
no Zama name used in README, docs, or marketing
- NOTICE file provides factual attribution per legal best practice
(not endorsement; required by upstream BSD-3-Clause-Clear)
README + NOTICE rewritten from scratch with Lux brand:
- Quick-start in Python (torus.fhe)
- Architecture diagram showing the gen-1 vtbl integration path
(luxcpp/gpu → lux-private/gpu-kernels for CUDA/Metal/WebGPU)
- Scheme coverage table: TFHE (luxfi/fhe), CKKS/BGV/BFV (luxfi/lattice)
- Lux FHE family table: Torus / TorusVM / TorusEVM / TorusML / TorusNet
Known limitations (phase-2A scope):
- PyPI package torus-fhe not yet published; the torus Python module
is renamed structurally but pip-installable distribution is a
follow-up (Phase 2A.1)
- MLIR dialect rename is text-level; the compiler-internal LLVM
rebuild (concrete-compiler-internal-llvm-project submodule) is
structural and works; tablegen files renamed concrete→torus but the
generated .inc files in the source tree will regenerate at build
time
- backends/torus-cuda/implementation/ is an upstream submodule
pointer to the tfhe-rs source (not fetched in the staging clone);
the CUDA backend body is delivered out-of-tree
- ~100 test-fixture variable names like concrete_encoded_sample
retain "concrete" as a math term (vs symbolic); these are inside
tests/, not the public API; cleanup is a follow-up commit
- 295 Python `from concrete import ...` residuals in luxfhe/ml-sdk
consumer remain; that repo's import update is Phase 2B
This commit is the seed for the luxfhe/torus repo. Push as the first
commit to a fresh GitHub repo; do not re-import upstream Zama git
history.
1.3 KiB
1.3 KiB
Using round/truncate bit pattern before table lookups
This guide teaches how to improve the execution time of Torus circuits by using some special operations that reduce the bit width of the input of the table lookup.
There are two extensions which can reduce the bit width of the table lookup input, fhe.round_bit_pattern(...) and fhe.truncate_bit_pattern(...), which can improve performance by sacrificing exactness.
For example the following code:
import numpy as np
from torus import fhe
inputset = fhe.inputset(fhe.uint10)
for lsbs_to_remove in range(0, 10):
def f(x):
return fhe.round_bit_pattern(x, lsbs_to_remove) // 2
compiler = fhe.Compiler(f, {"x": "encrypted"})
circuit = compiler.compile(inputset)
print(f"{lsbs_to_remove=} -> {int(circuit.complexity):>13_} complexity")
prints:
lsbs_to_remove=0 -> 9_134_406_574 complexity
lsbs_to_remove=1 -> 3_209_430_092 complexity
lsbs_to_remove=2 -> 1_536_476_735 complexity
lsbs_to_remove=3 -> 1_588_749_586 complexity
lsbs_to_remove=4 -> 848_133_081 complexity
lsbs_to_remove=5 -> 525_987_801 complexity
lsbs_to_remove=6 -> 358_276_023 complexity
lsbs_to_remove=7 -> 373_311_341 complexity
lsbs_to_remove=8 -> 400_596_351 complexity
lsbs_to_remove=9 -> 438_681_996 complexity