Deterministic GPU-accelerated mathematical computation for safety-critical AI infrastructure. 72.7M ops/sec validated (up to 8.3B with FP16 tensor cores) with bit-exact reproducibility. No symbolic math. No Python overhead. Just fast, safe, predictable expression evaluation.
Enterprise-grade SIMD microservice built with memory-safe Rust • Patent Pending
Bit-exact reproducible results across runs. Guaranteed 55ms latency for 4M elements—no variance. Memory-safe Rust with zero unsafe code in hot paths. Aerospace/automotive certification ready.
72.7M validated (FP32). Up to 8.3B optimized with FP16 tensor cores + batching (Phase 1 roadmap). 377× faster than SIMD baseline. Cross-platform SIMD (AVX-512/AVX2/ARM Neon).
Better CPU energy efficiency per operation, validated benchmarks. ARM64 Neon at 400M ops/J for edge deployment.
CPU peak throughput (edge hardware)
NVIDIA L4 with FP16 tensor cores (240 cores) + batching. 72.7M validated FP32 baseline. 377× faster than SIMD baseline.
Hyperscale patterns verified at production scale
Industry-leading efficiency class for CPU
/evaluate - Vectorized y=f(x) over arrays
/bisect - Root-finding with bracket [lo, hi]
/bisect_auto - Auto-bracket from guess
/health - Service health probe
Clear boundaries prevent feature creep and set accurate expectations
Use SymPy instead if you need: Symbolic differentiation, equation solving, simplification
Why it matters: Symbolic preprocessing adds latency variance. LuxiEdge guarantees 55ms for 4M elements—no variance. Symbolic operations break this guarantee.
Example:
• SymPy: d/dx(x² + sin(x)) → Symbolic derivative
• LuxiEdge: Evaluate 2x + cos(x) at GPU speed
Use JAX/TensorFlow instead if you need: Automatic differentiation, graph compilation, training loops, research workflows
Why it matters: General frameworks add graph compilation overhead and Python layers. LuxiEdge is purpose-built for explicit expression evaluation—no graph, no compilation, just fast deterministic math.
Example:
• JAX: jax.grad(lambda x: x**2 + sin(x)) → Auto-diff
• LuxiEdge: Evaluate 2*x + cos(x) at 72.7M–8.3B ops/sec GPU
LuxiEdge is a stateless HTTP/gRPC microservice, not a Python library.
Why it matters: Embedding Python would eliminate our 36,363× speedup over interpreted evaluation. We intentionally avoid Python overhead.
# NOT: pip install luxiedge
# YES: HTTP POST to /evaluate endpoint
curl -X POST http://localhost:8080/evaluate \
-d '{"expression": "sin(x) * cos(x)", "x": [1.0, 2.0, 3.0]}'
LuxiEdge evaluates explicit expressions: y = f(x)
Why it matters: Implicit solving requires iterative methods with variable iteration counts = variable latency. This breaks our deterministic execution guarantee.
Example:
• ❌ LuxiEdge can't solve: x² + y² = 1 (implicit)
• ✅ LuxiEdge can evaluate: y = sqrt(1 - x²) (explicit)
Workaround: Convert implicit to explicit form, then use LuxiEdge.
Use NumPy for: General array operations, linear algebra, broadcasting
LuxiEdge complements NumPy for: Mathematical expression evaluation at GPU speed
import numpy as np
x = np.linspace(0, 2*np.pi, 1000) # NumPy: Generate data
# LuxiEdge: Evaluate expression at GPU speed
response = requests.post('http://localhost:8080/evaluate', ...)
Use xsimd/Highway if you need: Custom SIMD intrinsics, hand-optimized kernels
LuxiEdge provides: Pre-optimized cross-platform SIMD (AVX-512/AVX2/ARM Neon) with automatic runtime selection. No custom coding needed.
A specialized mathematical computation platform that:
Perfect for safety-critical AI infrastructure: Grok, Autopilot, Optimus, SpaceX orbital mechanics
Understanding where LuxiEdge excels vs. general frameworks
JAX excels at ML research with automatic differentiation and JIT compilation. LuxiEdge delivers production-grade deterministic execution for safety-critical systems where bit-exact reproducibility matters more than research flexibility. 72.7M–8.3B ops/sec GPU throughput (FP32 validated, FP16 optimized).
LuxiEdge Advantage:
CuPy provides GPU-accelerated NumPy operations with Python integration. LuxiEdge offers 72.7M–8.3B ops/sec with deterministic latency guarantees and cross-platform SIMD optimization (x86/ARM/GPU) beyond just GPU.
LuxiEdge Advantage:
TensorFlow is a general ML framework with graph compilation overhead. LuxiEdge is purpose-built mathematical computation with 36,363× speedup over interpreted evaluation and memory-safe Rust architecture.
LuxiEdge Advantage:
NumExpr optimizes CPU-based NumPy expressions (0.95-4x speedup). LuxiEdge adds GPU acceleration (72.7M–8.3B ops/sec), deterministic execution, and cross-platform SIMD for real-time control systems.
LuxiEdge Advantage:
SymPy solves symbolic math problems (differentiation, simplification, solving). LuxiEdge evaluates explicit expressions at GPU speed with deterministic results. Complementary, not competitive.
LuxiEdge Advantage:
Real-time expression evaluation for manufacturing automation, process control systems, and robotics motion planning with deterministic latency guarantees.
Accelerate pre/post-processing for machine learning workloads, data normalization, feature engineering, and batch transformations. Neural surrogate models achieve 9× speedup over native inference.
Power path planning, sensor fusion calculations, and real-time decision-making for autonomous vehicles, drones, and navigation systems.
Reduce compute costs for data centers, cloud platforms, and hyperscale deployments through race-to-idle efficiency and reduced cooling overhead.
Fast root-finding for Lambert's Problem and satellite trajectory optimization. Multi-revolution swarm solving enables rapid mission planning for space applications.
Luxi™ is available for white-label licensing, strategic partnerships, and custom enterprise deployments. Our NDA Partner Program provides early access to roadmap features and dedicated integration support.
Deploy under your brand with custom SLAs and support agreements
Patent Pending • Commercial license (LicenseRef-Luxi-Business-1.0) with NDA coverage
Direct engineering access and custom integration guidance