Realising the Full Potential of Multi-core Designs
Multi-core chips offer performance, scalability, low-power and flexibility, but are they useable by software engineers? New start-up, Ignios, is addressing these issues.
ASIC, ASSP, FPGA and other System on Chip (SoC) designs containing multiple processor cores are becoming the preferred hardware platforms for many applications. Compared with uni-processor architectures, multi-core chips have the potential to provide a far higher level of price-performance. These chips combine specialist engines within a single design, which may include any configuration of multiple CPUs, DSPs and co-processors. With multi-core, a new class of flexible software-programmable designs are permeating the SoC and merchant semiconductor market. According to analysts, the multi-processor SoC segment is forecast to grow at a compound annual rate of around 30 percent.
Recent multi-core commercial designs target applications such as network processors, recordable DVDs, set-top boxes, HDTV platforms, mobile handsets and many others. The number of cores within a single design ranges from a couple to over 150. The most prevalent example of a multi-core application is the ubiquitous mobile handset; many GSM devices contain a single digital chip comprising a DSP for baseband processing and a general-purpose processor for handling the application requirements.
Click here to read more ...
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
- Realising the Full Potential of Multi-core Designs
- The Benefits of a Multi-Protocol PMA
- Ramping Up Open-Source RISC-V Cores: Assessing the Energy Efficiency of Superscalar, Out-of-Order Execution
- Reusable debug infrastructure in multi core SoC : Embedded WiFi case study
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