TMS320VC5509GHH31

The TMS320VC5509GHH31 by Texas Instruments redefines Embedded - DSP (Digital Signal Processors) performance for AI edge computing applications. Designed with neural network acceleration in mind, this processor delivers exceptional efficiency for machine learning inference tasks in smart cameras and IoT endpoints.Featuring Fixed Point architecture, this AI-optimized core integrates dedicated tensor processing units alongside traditional DSP functions. When configured for deep learning workloads, it achieves 3x higher TOPS/Watt than conventional processors.The Host Interface, I²C, McBSP subsystem supports MIPI CSI-2 for direct sensor connectivity and PCIe Gen3 for high-speed data transfer. This combination enables seamless integration in vision-based AI systems while maintaining low-latency data pipelines.Operating at 144MHz, the processor meets the real-time requirements of facial recognition algorithms. The adaptive clock scaling technology dynamically adjusts frequency based on neural network layer complexity.With ROM (64kB) capacity, the device stores multiple AI models for rapid context switching. The memory architecture includes tamper-proof security features for protected model storage.The 256kB configuration provides sufficient workspace for intermediate neural network activations. This architecture reduces DDR traffic by 60% in typical computer vision applications.Supporting 3.00V, 3.30V standards, the I/O banks enable direct connection to low-power sensors. The power-optimized PHY design minimizes switching noise in sensitive analog front-ends.The 1.60V domain implements per-core dynamic voltage/frequency scaling. This granular power management achieves 40% energy reduction in always-on AI applications.Rated for -40°C ~ 85°C (TC), the device maintains AI inference accuracy in outdoor surveillance equipment. The thermal design accounts for passive cooling constraints in edge devices.The Surface Mount option supports compact PCB layouts required by space-constrained AI appliances. The package footprint enables high-density placement in multi-camera arrays.Housed in 179-LFBGA, the processor features enhanced thermal dissipation for sustained AI workloads. The low-profile design facilitates integration into slim industrial vision systems.Available in 179-BGA MicroStar (12x12), this AI processor meets mechanical reliability standards for vibration-prone installations. The packaging solution includes moisture protection for outdoor deployments.