# Ankhdjet: An Open-Source Compiler for Mask-Programmed Ternary Compute-in-ROM on an Open PDK

arXiv: https://arxiv.org/abs/2608.26206 · HTML: https://mlsanity.com/paper/2608.26206/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 10 of its 36 references that are in the map.
- First posted on arXiv 26 Aug 2026.

## Builds on (most cited first, 10 of 10)

- [The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits](https://mlsanity.com/paper/2402.17764/) (2024)
- [BitNet b1.58 2B4T Technical Report](https://mlsanity.com/paper/2504.12285/) (2025)
- [Bitnet.cpp: Efficient Edge Inference for Ternary LLMs](https://mlsanity.com/paper/2502.11880/) (2025)
- [TeLLMe: An Energy-Efficient Ternary LLM Accelerator for Prefilling and Decoding on Edge FPGAs](https://mlsanity.com/paper/2504.16266/) (2025)
- [OpenSpike: An OpenRAM SNN Accelerator](https://mlsanity.com/paper/2302.01015/) (2023)
- [SynDCIM: A Performance-Aware Digital Computing-in-Memory Compiler with Multi-Spec-Oriented Subcircuit Synthesis](https://mlsanity.com/paper/2411.16806/) (2024)
- [BitROM: Weight Reload-Free CiROM Architecture Towards Billion-Parameter 1.58-bit LLM Inference](https://mlsanity.com/paper/2509.08542/) (2025)
- [OpenACM: An Open-Source SRAM-Based Approximate CiM Compiler](https://mlsanity.com/paper/2601.11292/) (2026)
- [HighTide: An Agent-Curated Open-Source VLSI Benchmark Suite](https://mlsanity.com/paper/2606.04126/) (2026)
- [TOM: A Ternary Read-only Memory Accelerator for LLM-powered Edge Intelligence](https://mlsanity.com/paper/2602.20662/) (2026)

## Abstract (arXiv)

Large-language-model inference is dominated by weight movement: every generated token re-reads every weight. Ternary quantization (BitNet b1.58) shrinks each weight to 1.58 bits with reported parity at the 2B-parameter scale, small enough that hardwiring the weights into a read-only mask becomes plausible, and a commercial chip (Taalas HC1) has validated hardwired weights on an advanced node behind closed tooling. This paper asks whether model-specific silicon can be made reproducible with entirely open infrastructure. We present Ankhdjet, an open-source compiler that lowers a HuggingFace ternary checkpoint (BitNet b1.58 and its kin) to a via-mask program of a fixed compute-in-ROM macro on the open SKY130 PDK, verified end to end with open tools. We defend two claims: (1) the first open-source weights-to-mask compute-in-ROM compiler on a fabricable open PDK, taken through full open-toolchain signoff (KLayout DRC zero, netgen LVS zero, clean timing) twice with two different weight matrices through an identical flow in which only the mask differs; and (2) the first compute-in-ROM macro submitted for fabrication on an open PDK (TinyTapeout/ChipFoundry SKY130 shuttle ttsky26c, silicon expected 2027). The compiler's read is fully digital (full-swing bitline sampling into standard cells, so the emission ports to any node by synthesis); an analog comparator readout of the same machine is retained as a measured variant, replaced by the digital readout at one eighth the area. We additionally report the per-level adversarial verification methodology that caught three DRC-invisible silent shorts, a negative result on storing two ternary weights per transistor at 130 nm, and which analog sense techniques survive at which nodes. Read energy is from extracted-parasitic simulation (0.98-1.73 pJ per sensed weight); no energy measurements are claimed, and the fabricated vehicles are demonstrators.