Page 309 - AI for Good Innovate for Impact

AI for Good Innovate for Impact

Our Solution

The Venus initiative delivers a comprehensive ecosystem incorporating silicon (Venus),
toolchains (Zoozve), and software stacks (Echo). The Venus Chip Architecture [6], implemented
in 40nm technology, pioneers the world's first RISC-V domain-specific architecture that fuses AI 4.3 - 5G
and communications. Innovative features include a cacheless manycore architecture eliminating
energy waste through dataflow-driven computing, optimized for wireless baseband processing
(WBP); hierarchical dataflow scheduling that abstracts WBP into Directed Acyclic Graphs, using
a "Pack-n-Ship" mechanism to reduce data transfer overhead by 60%; and heterogeneous
configurable clusters supporting dynamic core combinations, achieving 288Mbps link
throughput on SMIC 40nm prototypes with FFT/BP algorithm performance reaching 2.3x/2x that
of commercial hardware. Additionally, the Zoozve Compiler introduces the first "Strip-Mining-
Free" RISC-V vector extension compiler. It features an asymmetric instruction set, eliminating
strip-mining overhead for ultra-long vector operations, reducing dynamic instruction counts
by 344x/76x for FFT/DOT; arbitrary register grouping to overcome fixed-register constraints
in RVV, optimizing AI operations like 2D convolution; and a heterogeneous compilation
framework that unifies CPU/NPU memory management, leading to 7.06x higher code density
and 5.58x memory efficiency in CNN models. Lastly, the Echo Testbench serves as an open-
source wireless testbed providing a full-stack development environment. It includes a high-
performance operator library covering 5G/4G/GNSS/LoRa and AI operators, comparable to
Intel AVX/ARM Neon; a three-layer programming model consisting of a task layer (modules in
Venus ISA), a DAG layer (network assembly via .bas files), and a scheduler layer (L1 hardware
control); and full-stack emulation that enables closed-loop development, significantly reducing
traditional baseband R&D costs.

Validation and Application Scenarios

FPGA prototypes have demonstrated viability across three critical scenarios: RedCap
Lightweight Terminals have successfully completed commercial base station communication
tests, validating architectural support for mid-low-speed IoT; high-precision GNSS positioning
achieves low-power, full-band reception for autonomous vehicles and drones; and AI-enhanced
communications develop real-time AI ionospheric delay prediction algorithms, showcasing
communication-sensing-intelligence fusion. The testbed has open-sourced all LTE/NR PHY
modules and foundational AI operators, with full protocol stack implementation forthcoming.

Conclusion

The Venus project represents a paradigm shift in baseband processing. Technically, it achieves
the first ISA-level fusion of communications and AI on RISC-V DSA, overcoming the "impossible
trinity" of performance, efficiency, and elasticity through dataflow-driven manycore architecture.
Industrially, it constructs the first comprehensive open-source baseband stack, dismantling
closed ecosystems and providing operators with vendor-agnostic foundations. Ecologically,
the Echo testbed acts as a "PyTorch for wireless communications," accelerating the translation
between academia and industry. When questioned about the necessity of 6G, Venus responds
by emphasizing that the essence of 6G lies not in higher frequencies or more antennas, but in
transforming networks into intelligent entities through open architecture, laying the foundation
for future innovations.

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