An Agent-Driven End-to-End HW-SW Co-Design Benchmark for Heterogeneous SoCs (Columbia, IBM)
Researchers from Columbia University and IBM Research have released “HSCO-Bench: An Agent-Driven End-to-End Hardware-Software Co-design Benchmark for Systems-on-Chip”. Abstract “Large language models (LLMs) are adopted for software and hardware design, yet these domains are still evaluated separately. Software benchmarks typically assume fixed hardware targets, while hardware benchmarks focus on component-level optimization without considering the full... » read more The post An Agent-Driven End-to-End HW-SW Co-Design Benchmark for Heterogeneous SoCs (Columbia, IBM) appeared first on Semicondu
The increasing complexity of heterogeneous SoCs and the push for AI/ML integration necessitate new co-design methods to optimize performance and efficiency.
This research provides a standardized benchmark for evaluating hardware-software co-design using AI agents, which is crucial for advancing next-generation computing architectures.
The development and adoption of such benchmarks will accelerate the holistic design and optimization of complex silicon systems, moving beyond separate hardware and software evaluations.
- · Semiconductor companies
- · AI/ML accelerator developers
- · EDA tool providers
- · Academic research institutions
- · Traditional hardware design methodologies
- · Software teams isolated from hardware constraints
Improved performance and power efficiency of AI-enabled heterogeneous SoCs due to better co-design.
Faster iteration cycles and reduced development costs for new silicon architectures employing AI agents in design.
Democratization of advanced chip design through agent-driven automation, lowering barriers to entry for specialized silicon development.
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