ARCHITECTURE
7-Layer Architecture
Complete end-to-end system from NVIDIA Jetson hardware to industrial APIs.
Layer 7
Application Interface
REST API + WebSocket server
Python
Layer 6
Orchestration & Control
Execution loop, monitoring
Python
Layer 5
Industrial Integration
SLA Monitor, SEMI/GEM protocols
Python/C++
Layer 4
Model Architecture
Neural network implementation
Python
Layer 3
CUDA Acceleration
Custom GPU kernels
CUDA C++
Layer 2
Hardware Abstraction
Runtime & device management
Python/Shell
Layer 1
Physical Hardware
Jetson AGX Orin 64GB
Ampere GPU
CORE TECHNOLOGY
Built for speed
PERFORMANCE
Verified Performance
Benchmarks on Jetson AGX Orin 64GB · December 2025
Understanding the 111x Speedup
The baseline (~2588ms) represents PyTorch/TensorFlow running the same 64M parameter model with standard operations. NeuraTensor SDK's custom CUDA kernels achieve 23ms inference and 4x less memory through fused SNN-SSM operations, optimized memory patterns, and hardware-aware parallelization—delivering 111x faster performance.
Hardware Platform
GPU Subsystem
- →2048 CUDA cores @ 1.3 GHz
- →64 Tensor Cores (FP16/INT8)
- →Ampere Architecture (SM 8.7)
- →16 Streaming Multiprocessors
Memory & I/O
- →61.3GB unified LPDDR5 RAM
- →204.8 GB/s memory bandwidth
- →4MB L2 cache (shared)
- →Zero-copy CPU/GPU access