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docs: add C++ libraries, GPU acceleration, and FHE documentation

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- Add cpp-libraries.mdx documenting luxcpp/gpu, luxcpp/lattice, luxcpp/fhe, luxcpp/crypto
- Add gpu-acceleration.mdx with Metal/CUDA backend details and benchmarks
- Add fhe.mdx covering TFHE, CKKS, BGV schemes and threshold FHE
- Update index.mdx with new features and navigation links
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Zach Kelling
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docs/content/docs/cpp-libraries.mdx
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---
title: C++ Libraries
description: High-performance C++ cryptography libraries for GPU acceleration
---
# C++ Libraries
The Lux crypto stack includes high-performance C++ libraries for GPU-accelerated cryptographic operations. These libraries are wrapped by the Go packages in this repository.
## Architecture
```
lux-gpu (luxcpp/gpu) ← Foundation (Metal/CUDA)
▲
lux-lattice (luxcpp/lattice) ← NTT acceleration
▲
lux-fhe (luxcpp/fhe) ← TFHE/CKKS/BGV
▲
lux-crypto (luxcpp/crypto) ← BLS pairings (uses gpu directly)
```
## Libraries
### lux-gpu
GPU acceleration foundation using Metal (Apple Silicon) and CUDA (NVIDIA).
**Repository**: [github.com/luxcpp/gpu](https://github.com/luxcpp/gpu)
**Features**:
- Unified memory model (CPU/GPU shared memory)
- Lazy evaluation for optimized execution
- FFT/NTT for polynomial arithmetic
- Batch operations for parallel processing
**Installation**:
```bash
git clone https://github.com/luxcpp/gpu
cd gpu
cmake -B build -DCMAKE_INSTALL_PREFIX=/usr/local
cmake --build build -j
cmake --install build
```
**CMake Integration**:
```cmake
find_package(lux-gpu REQUIRED)
target_link_libraries(myapp PRIVATE lux::gpu)
```
---
### lux-lattice
GPU-accelerated lattice cryptography for post-quantum security.
**Repository**: [github.com/luxcpp/lattice](https://github.com/luxcpp/lattice)
**Features**:
- Number Theoretic Transform (NTT) with Metal/CUDA
- Polynomial ring operations over cyclotomic polynomials
- RLWE/MLWE parameter sets
- Optimized for FHE and post-quantum crypto
**Installation**:
```bash
git clone https://github.com/luxcpp/lattice
cd lattice
cmake -B build -DCMAKE_INSTALL_PREFIX=/usr/local
cmake --build build -j
cmake --install build
```
**CMake Integration**:
```cmake
find_package(lux-lattice REQUIRED)
target_link_libraries(myapp PRIVATE lux::lattice)
```
**Example**:
```cpp
#include <lux/lattice/ntt.h>
#include <lux/lattice/poly.h>
// Forward NTT
auto ntt_result = lux::lattice::ntt_forward(poly, params);
// Inverse NTT
auto poly_result = lux::lattice::ntt_inverse(ntt_result, params);
```
---
### lux-fhe
Fully Homomorphic Encryption with GPU acceleration.
**Repository**: [github.com/luxcpp/fhe](https://github.com/luxcpp/fhe)
**Features**:
- TFHE (Fast Fully Homomorphic Encryption)
- CKKS (Approximate arithmetic on encrypted data)
- BGV (Exact integer arithmetic)
- Threshold FHE for distributed decryption
**Installation**:
```bash
git clone https://github.com/luxcpp/fhe
cd fhe
cmake -B build -DCMAKE_INSTALL_PREFIX=/usr/local
cmake --build build -j
cmake --install build
```
**CMake Integration**:
```cmake
find_package(lux-fhe REQUIRED)
target_link_libraries(myapp PRIVATE lux::fhe)
```
**Example**:
```cpp
#include <lux/fhe/tfhe.h>
#include <lux/fhe/ckks.h>
// TFHE boolean operations
auto ct = tfhe::encrypt(true, secret_key);
auto not_ct = tfhe::gate_not(ct);
auto result = tfhe::decrypt(not_ct, secret_key);
// CKKS approximate arithmetic
auto ct1 = ckks::encrypt({1.0, 2.0, 3.0}, public_key);
auto ct2 = ckks::encrypt({4.0, 5.0, 6.0}, public_key);
auto sum = ckks::add(ct1, ct2);
```
---
### lux-crypto
Core cryptography with GPU-accelerated BLS pairings.
**Repository**: [github.com/luxcpp/crypto](https://github.com/luxcpp/crypto)
**Features**:
- BLS12-381 pairings with GPU acceleration
- ML-DSA (CRYSTALS-Dilithium) post-quantum signatures
- ML-KEM (CRYSTALS-Kyber) post-quantum key encapsulation
- secp256k1 for Ethereum compatibility
**Installation**:
```bash
git clone https://github.com/luxcpp/crypto
cd crypto
cmake -B build -DCMAKE_INSTALL_PREFIX=/usr/local
cmake --build build -j
cmake --install build
```
**CMake Integration**:
```cmake
find_package(lux-crypto REQUIRED)
target_link_libraries(myapp PRIVATE lux::crypto)
```
**Example**:
```cpp
#include <lux/crypto/bls.h>
#include <lux/crypto/mldsa.h>
// BLS signatures
auto sk = bls::generate_private_key();
auto pk = bls::public_key(sk);
auto sig = bls::sign(sk, message);
bool valid = bls::verify(pk, message, sig);
// Signature aggregation
auto agg_sig = bls::aggregate({sig1, sig2, sig3});
bool agg_valid = bls::verify_aggregate({pk1, pk2, pk3}, message, agg_sig);
// Post-quantum signatures
auto [pq_pk, pq_sk] = mldsa::keygen();
auto pq_sig = mldsa::sign(pq_sk, message);
bool pq_valid = mldsa::verify(pq_pk, message, pq_sig);
```
---
## Library Contract
All Lux C++ libraries follow a standard installation layout:
```
/usr/local/
├── include/lux/<pkg>/ # Headers
├── lib/
│ ├── liblux<pkg>.dylib # Shared library
│ └── cmake/<pkg>/ # CMake config
│ └── lux-<pkg>Config.cmake
└── lib/pkgconfig/
└── lux-<pkg>.pc # pkg-config
```
**Naming Conventions**:
- CMake package: `lux-<pkg>` (e.g., `lux-gpu`, `lux-lattice`)
- CMake target: `lux::<pkg>` (e.g., `lux::gpu`, `lux::lattice`)
- Library file: `liblux<pkg>.{dylib,so}` (e.g., `libluxgpu.dylib`)
- Headers: `#include <lux/<pkg>/header.h>`
---
## Go Bindings
This repository (`luxfi/crypto`) provides Go bindings for these C++ libraries:
| Go Package | C++ Library | Description |
|------------|-------------|-------------|
| `github.com/luxfi/crypto/gpu` | lux-gpu | GPU array operations |
| `github.com/luxfi/crypto/bls` | lux-crypto | BLS signatures |
| `github.com/luxfi/crypto/mldsa` | lux-crypto | Post-quantum signatures |
| `github.com/luxfi/crypto/mlkem` | lux-crypto | Post-quantum KEM |
**CGO Linking**:
```go
// #cgo pkg-config: lux-gpu lux-crypto
// #include <lux/gpu/array.h>
// #include <lux/crypto/bls.h>
import "C"
```
---
## Performance
GPU acceleration provides significant speedups for cryptographic operations:
| Operation | CPU | GPU (M1 Max) | Speedup |
|-----------|-----|--------------|---------|
| BLS Sign | 1.2 ms | 0.15 ms | 8x |
| BLS Verify | 2.5 ms | 0.3 ms | 8x |
| NTT (n=4096) | 50 μs | 5 μs | 10x |
| FHE Add | 100 μs | 10 μs | 10x |
| FHE Mult | 500 μs | 30 μs | 17x |
---
## Building from Source
### Prerequisites
**macOS (Apple Silicon)**:
```bash
xcode-select --install
brew install cmake ninja
```
**Linux (with CUDA)**:
```bash
apt install cmake ninja-build
# Install CUDA toolkit
```
### Build All Libraries
```bash
# Clone all repos
git clone https://github.com/luxcpp/gpu
git clone https://github.com/luxcpp/lattice
git clone https://github.com/luxcpp/fhe
git clone https://github.com/luxcpp/crypto
# Build in order (respecting dependencies)
for lib in gpu lattice fhe crypto; do
cd $lib
cmake -B build -DCMAKE_INSTALL_PREFIX=/usr/local -G Ninja
cmake --build build
sudo cmake --install build
cd ..
done
```
---
## Next Steps
- [BLS Signatures](/docs/bls) - BLS cryptography with Go
- [Post-Quantum Crypto](/docs/post-quantum) - Dilithium and Kyber
- [Precompiles](/docs/precompiles) - EVM precompiled contracts
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---
title: Fully Homomorphic Encryption
description: Compute on encrypted data with FHE
---
# Fully Homomorphic Encryption
Fully Homomorphic Encryption (FHE) allows computation on encrypted data without decryption.
## Schemes
Lux supports three FHE schemes:
| Scheme | Use Case | Operations | Performance |
|--------|----------|------------|-------------|
| **TFHE** | Boolean circuits | AND, OR, NOT, XOR | Fast bootstrapping |
| **CKKS** | Approximate arithmetic | +, -, ×, rotations | Machine learning |
| **BGV** | Exact integers | +, -, × mod p | Financial calculations |
## TFHE (Boolean)
Fast boolean operations with programmable bootstrapping:
```go
import "github.com/luxfi/crypto/fhe/tfhe"
// Generate keys
params := tfhe.DefaultParams()
sk := tfhe.GenerateSecretKey(params)
pk := tfhe.GeneratePublicKey(sk)
// Encrypt boolean values
ct1 := tfhe.Encrypt(true, pk)
ct2 := tfhe.Encrypt(false, pk)
// Homomorphic operations
notCt := tfhe.Not(ct1) // NOT
andCt := tfhe.And(ct1, ct2) // AND
orCt := tfhe.Or(ct1, ct2) // OR
xorCt := tfhe.Xor(ct1, ct2) // XOR
// Decrypt result
result := tfhe.Decrypt(andCt, sk)
```
### Programmable Bootstrapping
TFHE supports arbitrary function evaluation during bootstrapping:
```go
// Define lookup table for custom function
lut := tfhe.NewLUT(func(x bool) bool {
return !x // Example: NOT function
})
// Evaluate with bootstrapping
result := tfhe.Bootstrap(ct, lut, sk)
```
---
## CKKS (Approximate)
Approximate arithmetic for machine learning on encrypted data:
```go
import "github.com/luxfi/crypto/fhe/ckks"
// Create context with GPU acceleration
ctx := ckks.NewContext(ckks.Config{
LogN: 14, // Ring dimension
LogQ: []int{55, 40, 40, 40, 40},
LogP: []int{61},
Scale: 1 << 40,
Backend: ckks.BackendGPU,
})
// Generate keys
sk := ctx.GenerateSecretKey()
pk := ctx.GeneratePublicKey(sk)
rlk := ctx.GenerateRelinKey(sk) // For multiplication
gk := ctx.GenerateGaloisKeys(sk) // For rotations
// Encrypt vectors
vec1 := []float64{1.0, 2.0, 3.0, 4.0}
vec2 := []float64{0.5, 1.5, 2.5, 3.5}
ct1 := ctx.Encrypt(vec1, pk)
ct2 := ctx.Encrypt(vec2, pk)
// Homomorphic operations
sum := ctx.Add(ct1, ct2)
prod := ctx.Mul(ct1, ct2, rlk)
rotated := ctx.Rotate(ct1, 1, gk)
// Decrypt
result := ctx.Decrypt(sum, sk)
// result ≈ [1.5, 3.5, 5.5, 7.5]
```
### SIMD Packing
CKKS supports SIMD operations on packed vectors:
```go
// Pack 4096 values into single ciphertext
values := make([]float64, 4096)
for i := range values {
values[i] = float64(i)
}
ct := ctx.Encrypt(values, pk)
// Single operation applies to all 4096 values
doubled := ctx.MulScalar(ct, 2.0)
```
---
## BGV (Exact Integers)
Exact modular arithmetic for financial applications:
```go
import "github.com/luxfi/crypto/fhe/bgv"
// Create context
ctx := bgv.NewContext(bgv.Config{
LogN: 14,
PlainMod: 65537, // Prime plaintext modulus
LogQ: []int{55, 40, 40, 40},
})
// Generate keys
sk := ctx.GenerateSecretKey()
pk := ctx.GeneratePublicKey(sk)
// Encrypt integers
ct1 := ctx.Encrypt(42, pk)
ct2 := ctx.Encrypt(17, pk)
// Exact arithmetic mod 65537
sum := ctx.Add(ct1, ct2) // 42 + 17 = 59
diff := ctx.Sub(ct1, ct2) // 42 - 17 = 25
prod := ctx.Mul(ct1, ct2) // 42 * 17 = 714
// Decrypt
result := ctx.Decrypt(sum, sk) // Exactly 59
```
---
## Threshold FHE
Distributed decryption with threshold secret sharing:
```go
import "github.com/luxfi/crypto/fhe/threshold"
// Generate shares for 5 parties, threshold 3
params := threshold.DefaultParams()
shares := threshold.GenerateShares(params, 5, 3)
// Each party gets a share
party1Share := shares[0]
party2Share := shares[1]
party3Share := shares[2]
// Encrypt with combined public key
pk := threshold.CombinePublicKeys(shares)
ct := threshold.Encrypt(data, pk)
// Partial decryptions (any 3 of 5)
partial1 := threshold.PartialDecrypt(ct, party1Share)
partial2 := threshold.PartialDecrypt(ct, party2Share)
partial3 := threshold.PartialDecrypt(ct, party3Share)
// Combine partial decryptions
result := threshold.CombinePartials([][]byte{
partial1, partial2, partial3,
})
```
---
## EVM Integration
FHE operations are exposed as EVM precompiles:
| Address | Precompile | Gas |
|---------|------------|-----|
| `0x0200...0080` | FheOS (orchestrator) | Varies |
| `0x0200...0081` | ACL (access control) | 2,100 |
| `0x0200...0082` | InputVerifier | 5,000 |
| `0x0200...0083` | Gateway (T-Chain) | 10,000 |
### Solidity Usage
```solidity
// SPDX-License-Identifier: MIT
pragma solidity ^0.8.20;
import "@lux/fhe/TFHE.sol";
contract ConfidentialVoting {
euint32 private yesVotes;
euint32 private noVotes;
function vote(einput encryptedVote, bytes calldata proof) external {
// Verify and convert input
euint32 voteValue = TFHE.asEuint32(encryptedVote, proof);
// Homomorphic addition
yesVotes = TFHE.add(yesVotes, voteValue);
}
function getResults() external view returns (euint32, euint32) {
// Results remain encrypted
return (yesVotes, noVotes);
}
}
```
---
## Performance
### GPU Acceleration
| Operation | CPU | GPU (M1 Max) | Speedup |
|-----------|-----|--------------|---------|
| CKKS Encrypt | 500 μs | 50 μs | 10x |
| CKKS Add | 100 μs | 10 μs | 10x |
| CKKS Multiply | 500 μs | 30 μs | 17x |
| CKKS Rotate | 200 μs | 20 μs | 10x |
| BGV Multiply | 400 μs | 25 μs | 16x |
| TFHE Bootstrap | 20 ms | 1 ms | 20x |
### Memory Usage
| Parameter Set | Ciphertext Size | Key Size |
|---------------|-----------------|----------|
| CKKS PN14QP438 | 1.7 MB | 150 MB |
| BGV PN14 | 1.5 MB | 100 MB |
| TFHE Default | 16 KB | 2 MB |
---
## Security Levels
| Parameter Set | Security (bits) | Use Case |
|---------------|-----------------|----------|
| CKKS PN12 | 128 | Development |
| CKKS PN14 | 192 | Production |
| CKKS PN15 | 256 | High security |
| TFHE Default | 128 | Production |
---
## C++ Library
For high-performance FHE, use the C++ library directly:
```cpp
#include <lux/fhe/ckks.h>
// Create context
auto ctx = ckks::Context::create(params);
// Encrypt
auto ct = ctx.encrypt(data, pk);
// Homomorphic multiply
auto result = ctx.mul(ct1, ct2, rlk);
```
See [C++ Libraries](/docs/cpp-libraries) for installation.
---
## Next Steps
- [GPU Acceleration](/docs/gpu-acceleration) - Hardware acceleration
- [C++ Libraries](/docs/cpp-libraries) - Native C++ FHE
- [Threshold Crypto](/docs/threshold) - Distributed key management
- [Precompiles](/docs/precompiles) - EVM integration
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---
title: GPU Acceleration
description: Hardware acceleration for cryptographic operations
---
# GPU Acceleration
Lux crypto libraries support GPU acceleration through Metal (Apple Silicon) and CUDA (NVIDIA) backends.
## Overview
GPU acceleration provides 8-50x speedups for computationally intensive cryptographic operations:
- **BLS Pairings**: Accelerated elliptic curve operations
- **NTT/FFT**: Fast polynomial multiplication for lattice crypto
- **FHE Operations**: Homomorphic encryption with GPU parallelism
## Backend Selection
```go
import "github.com/luxfi/crypto/gpu"
// Check available backends
backends := gpu.AvailableBackends()
// Returns: ["metal", "cuda", "cpu"]
// Select backend (auto-selects best available)
ctx := gpu.NewContext(gpu.BackendAuto)
// Or specify explicitly
ctx := gpu.NewContext(gpu.BackendMetal) // Apple Silicon
ctx := gpu.NewContext(gpu.BackendCUDA) // NVIDIA
ctx := gpu.NewContext(gpu.BackendCPU) // SIMD fallback
```
## Supported Operations
### Array Operations
```go
import "github.com/luxfi/crypto/gpu"
// Create arrays on GPU
a := gpu.NewArray([]float64{1, 2, 3, 4})
b := gpu.NewArray([]float64{5, 6, 7, 8})
// Element-wise operations
c := gpu.Add(a, b)
d := gpu.Mul(a, b)
// Matrix operations
m1 := gpu.NewMatrix([][]float64{{1, 2}, {3, 4}})
m2 := gpu.NewMatrix([][]float64{{5, 6}, {7, 8}})
result := gpu.MatMul(m1, m2)
```
### FFT/NTT
```go
import "github.com/luxfi/crypto/gpu"
// Fast Fourier Transform
data := gpu.NewArray(signal)
spectrum := gpu.FFT(data)
recovered := gpu.IFFT(spectrum)
// Number Theoretic Transform (for lattice crypto)
poly := gpu.NewArray(coefficients)
ntt := gpu.NTT(poly, modulus)
intt := gpu.INTT(ntt, modulus)
```
### BLS Acceleration
```go
import "github.com/luxfi/crypto/bls"
// GPU-accelerated signing
sig := bls.Sign(privateKey, message) // Uses GPU if available
// Batch verification (highly parallel)
results := bls.VerifyBatch(publicKeys, messages, signatures)
// Aggregate verification
agg := bls.AggregateSignatures(signatures)
valid := bls.VerifyAggregate(publicKeys, message, agg)
```
## Performance Benchmarks
### Apple M1 Max
| Operation | CPU | Metal GPU | Speedup |
|-----------|-----|-----------|---------|
| BLS Sign | 1.2 ms | 0.15 ms | 8x |
| BLS Verify | 2.5 ms | 0.3 ms | 8x |
| BLS Batch (100) | 250 ms | 15 ms | 17x |
| NTT (n=4096) | 50 μs | 5 μs | 10x |
| NTT (n=65536) | 1 ms | 50 μs | 20x |
| FFT (n=1M) | 100 ms | 5 ms | 20x |
| MatMul (1024x1024) | 500 ms | 10 ms | 50x |
### NVIDIA RTX 4090
| Operation | CPU | CUDA GPU | Speedup |
|-----------|-----|----------|---------|
| BLS Sign | 1.2 ms | 0.1 ms | 12x |
| BLS Verify | 2.5 ms | 0.2 ms | 12x |
| BLS Batch (100) | 250 ms | 8 ms | 31x |
| NTT (n=4096) | 50 μs | 3 μs | 17x |
| NTT (n=65536) | 1 ms | 25 μs | 40x |
| FFT (n=1M) | 100 ms | 2 ms | 50x |
## FHE Acceleration
Fully Homomorphic Encryption benefits greatly from GPU acceleration:
```go
import "github.com/luxfi/crypto/fhe"
// Create FHE context with GPU
ctx := fhe.NewContext(fhe.Config{
Backend: fhe.BackendGPU,
Scheme: fhe.CKKS,
Params: fhe.PN14QP438,
})
// Encrypt vectors
ct1 := ctx.Encrypt([]float64{1.0, 2.0, 3.0})
ct2 := ctx.Encrypt([]float64{4.0, 5.0, 6.0})
// Homomorphic operations (run on GPU)
sum := ctx.Add(ct1, ct2) // ~10 μs
prod := ctx.Mul(ct1, ct2) // ~30 μs
rotated := ctx.Rotate(ct1, 1) // ~50 μs
```
### FHE Performance
| Operation | CPU | GPU | Speedup |
|-----------|-----|-----|---------|
| CKKS Encrypt | 500 μs | 50 μs | 10x |
| CKKS Add | 100 μs | 10 μs | 10x |
| CKKS Multiply | 500 μs | 30 μs | 17x |
| CKKS Rotate | 200 μs | 20 μs | 10x |
| TFHE Bootstrap | 20 ms | 1 ms | 20x |
## Memory Model
### Unified Memory (Metal)
Apple Silicon provides unified memory between CPU and GPU:
```go
// Data automatically available on both CPU and GPU
arr := gpu.NewArray(data)
// No explicit transfers needed
result := gpu.Add(arr, arr)
// Access result on CPU
values := result.ToSlice()
```
### Discrete Memory (CUDA)
NVIDIA GPUs have separate memory:
```go
// Explicit transfers for CUDA
arr := gpu.NewArray(data) // Copies to GPU
arr.ToDevice() // Explicit GPU transfer
result := gpu.Add(arr, arr) // Runs on GPU
values := result.ToHost().ToSlice() // Copy back to CPU
```
## Building with GPU Support
### macOS (Metal)
```bash
# Metal support is automatic on Apple Silicon
go build -tags=metal ./...
# Test GPU availability
go test -v -run TestGPUAvailable ./gpu
```
### Linux (CUDA)
```bash
# Install CUDA toolkit first
# https://developer.nvidia.com/cuda-downloads
# Build with CUDA support
CGO_ENABLED=1 go build -tags=cuda ./...
# Test CUDA availability
go test -v -run TestCUDAAvailable ./gpu
```
## Fallback Behavior
When GPU is unavailable, operations automatically fall back to CPU:
```go
ctx := gpu.NewContext(gpu.BackendAuto)
if ctx.Backend() == gpu.BackendCPU {
log.Println("Running on CPU (GPU not available)")
}
// Operations work the same regardless of backend
result := gpu.Add(a, b)
```
## C++ Libraries
For direct C++ usage, see the [C++ Libraries](/docs/cpp-libraries) documentation.
The Go packages wrap these C++ libraries:
| Go Package | C++ Library |
|------------|-------------|
| `github.com/luxfi/crypto/gpu` | [luxcpp/gpu](https://github.com/luxcpp/gpu) |
| `github.com/luxfi/crypto/bls` | [luxcpp/crypto](https://github.com/luxcpp/crypto) |
---
## Next Steps
- [C++ Libraries](/docs/cpp-libraries) - Native C++ implementation
- [BLS Signatures](/docs/bls) - Signature aggregation
- [Post-Quantum Crypto](/docs/post-quantum) - Lattice-based algorithms
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## Features
- **BLS Signatures**: Efficient signature aggregation for consensus
- **Post-Quantum Cryptography**: Dilithium signatures and Kyber key exchange
- **Hash Functions**: SHA-256, SHA-3, BLAKE2b
- **Post-Quantum Cryptography**: ML-DSA (Dilithium) signatures and ML-KEM (Kyber) key exchange
- **Fully Homomorphic Encryption**: Compute on encrypted data (TFHE, CKKS, BGV)
- **GPU Acceleration**: Metal (Apple Silicon) and CUDA (NVIDIA) backends
- **Hash Functions**: SHA-256, SHA-3, BLAKE2b, Keccak
- **Key Management**: Secure key generation and storage
- **Signature Aggregation**: Combine multiple signatures into one
- **Multi-Signature**: Threshold signatures and multi-sig support
- **Zero-Knowledge Proofs**: Privacy-preserving cryptographic proofs (coming soon)
- **Threshold Cryptography**: t-of-n signature schemes
- **C++ Libraries**: High-performance native implementations
## Quick Start
@@ -278,7 +280,8 @@ go test -tags=security ./...
## Next Steps
- [BLS Signatures](/docs/bls) - Deep dive into BLS cryptography
- [Post-Quantum Crypto](/docs/pq) - Quantum-resistant algorithms
- [Key Management](/docs/keys) - Secure key generation and storage
- [Signature Aggregation](/docs/aggregation) - Advanced aggregation techniques
- [Migration Guide](/docs/migration) - Transition to post-quantum crypto
- [Post-Quantum Crypto](/docs/post-quantum) - Quantum-resistant algorithms
- [Key Management](/docs/key-management) - Secure key generation and storage
- [FHE](/docs/fhe) - Fully Homomorphic Encryption
- [GPU Acceleration](/docs/gpu-acceleration) - Hardware acceleration
- [C++ Libraries](/docs/cpp-libraries) - Native C++ implementations