The dominance of GPUs in AI workloads has long been driven by their ability to handle massive parallelism, but this advantage comes at the cost of high-power consumption and architectural rigidity. A new approach, leveraging a chiplet-based RISC-V vector processor, offers an alternative that balances performance, efficiency,… Read More
Author: Jonah McLeod
Harnessing Modular Vector Processing for Scalable, Power-Efficient AI Acceleration
An Open-Source Approach to Developing a RISC-V Chip with XiangShan and Mulan PSL v2
As RISC-V gains traction in the global semiconductor industry, developers are exploring fully open-source approaches to processor design. XiangShan, a high-performance RISC-V CPU project, combined with the Mulan Permissive License v2 (Mulan PSL v2), represents a community-driven, transparent alternative to proprietary… Read More
MediaTek Develops Chip Utilizing TSMC’s 2nm Process, Achieving Milestones in Performance and Power Efficiency