SigTekX

>_ GPU-Accelerated Signal Processing Engine v0.9.5

System Purpose

SigTekX is a high-performance research platform architected for real-time ionospheric scintillation analysis. It bridges the gap between low-level CUDA optimization and high-level Python research workflows, providing sub-millisecond processing latency for ULF/VLF radio signal monitoring.

Core Performance

  • Sub-millisecond end-to-end latency
  • Zero-copy lock-free streaming architecture
  • CUDA/cuFFT accelerated spectral analysis
  • 100% real-time compliance at 100 kHz

Real-Time Streaming Executor

The Streaming Executor is the core of the engine's real-time capabilities. It employs a lock-free Single-Producer Single-Consumer (SPSC) ring buffer to decouple data acquisition from GPU processing.

C++ Streaming Executor Sequence
FIG 01: Sequence diagram of the Streaming Executor lifecycle.

Zero-Copy Memory Architecture

Direct DMA Access

The streaming critical path utilizes a peek_frame() API for direct DMA from Pinned Host memory, reducing the H2D latency floor.

Lock-Free SPSC Design

Data ingestion and processing are synchronized via atomic head/tail pointers to prevent thread contention.

C++ Streaming Memory Management Diagram
FIG 02: Memory architecture illustrating the zero-copy flow.

Benchmarked Performance

METRICVALUESPECIFICATION
Mean Latency160.1 μsRTX 3090 Ti | NFFT=4096
Throughput4,549 FPS~37.3M samples/sec
Real-time Compliance100%Zero deadline misses at 100 kHz
Accuracy (SNR)>123 dBIEEE 754-2019 FMA Compliant

Methods Paper Roadmap

Dual-Plane Architecture

Decoupling the Data Plane (C++/CUDA) from the Control Plane (Python).

Custom Stage Ecosystem

Integration of Numba CUDA kernels and PyTorch models directly into the data plane.

Performance Targets

Validation of a Real-Time Factor (RTF) ≤ 0.33 for ionospheric workloads.

Embedded Deployment

Transitioning workstation GPUs to power-constrained embedded systems (NVIDIA Jetson).

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