Managing intelligent I/O processing on DSP + GPP SoCs
Loc Truong, Texas Instruments
EETimes (6/7/2011 12:08 AM EDT)
This Product How-To article about TI’s OMAP-L138 C6-Integra DSP + ARM processor details the steps a developer needs to follow in building an application that must balance I/O processing tasks between a general purpose microcontroller and a digital signal processor.
DSP system developers face a difficult task of choosing options to meet increasing system performance requirements. Up the speed, optimize the code, add more processors, or even all of the above! It’s possible, but the developers must partition code intelligently between the general purpose processor and digital signal processors (DSPs) to make the best use of their architectures.
For instance, certain input/output (I/O) tasks can be offloaded to the general purpose processor (GPP) to implement smart I/O processing with features such as predictive caching, buffer parsing, sequencing and more.
Adding an obstacle, the developer may need to change the functionality of the system down the road and must have the flexibility to change the roles of each core to make sure hard and soft real-time can be met.
System developers must also decide if an operating system is needed, and if so, how to make sure the system-level I/O throughput comes closer to theoretical raw throughput maximums. I will examine the options a DSP system developer faces when partitioning I/O processing tasks and how to best implement the GPP in certain cases.
To read the full article, click here
Related Semiconductor IP
- AXI to UCIe FDI Interface IP
- 45SPCLO UCIe-Class 1-32Gbps Low Power Receiver IP (NRZ)
- 45SPCLO UCIe-Class 1-32Gbps Low Power Transmitter IP (NRZ)
- Peripheral Sensor Interface (PSI5) Host Controller
- Link Acceleration Unit
Related Articles
- What's your sine? Finding the right algorithm for digital frequency synthesis on a DSP
- Digital Signal Processing (DSP) Verification
- Building Process For the C/C++ Program on Complex SoCs
- IO and multiprotocol processing in highly demanding embedded architectures
Latest Articles
- CHIA: An open-source framework for principled, agentic AI-driven hardware/software co-design research
- Croc: Training the Next Generation Chip Designers on Domain-Specific End-to-End Open Source Silicon
- Design and Development of a Neuromorphic Silicon Suite: PVT Sensing, Stochastic LIF Inference, On-Chip STDP Learning, and Crossbar Programming
- LLM4RTL: Tool-Assisted LLM for RTL Generation
- Towards Delta Aware Training: Efficient DNN Weight Storage for Resource-Constrained FPGAs