This content will become publicly available on June 1, 2027
Retargeting Matters: General Motion Retargeting for Humanoid Motion Tracking
- Award ID(s):
- 2153854
- PAR ID:
- 10704998
- Publisher / Repository:
- IEEE International Conference on Robotics and Automation
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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During chip development, engineers must target different technologies, such as simulation and various ASIC and FPGA technologies. Conventionally, they split parts of the code (e.g., memories) into separate technology-specialized blocks implementing the same high-level behavior. This leads to brittle code, with multiple but subtly different blocks describing the same semantic behavior, harming verification, agility, and extensibility. We propose fungible memories, an HDL-level write once, map anywhere memory abstraction with rich enough semantics to automatically target all relevant technologies using a single generic interface. We incorporate fungible memories into a compiler called Memo. For designs without a specific technology mapping, we also present a memory decompiler which lifts memories from an existing gate-level design to Memo, enabling automated technology re-targeting, which is a holy grail for digital designers. We present a structure-aware equality saturation technique which scales to netlists with millions of cells and identifies memories that the state of the art cannot. We demonstrate that Memo effectively targets backends across different technology platforms (simulation, ASIC, and FPGA) over a suite of representative designs, including a RISC-V multicore SoC.more » « less
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