{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/instruction-set-architecture-isa-for","title":"Instruction Set Architecture (ISA) for Processing-in-Memory DNN Accelerators","arxiv_id":"2308.06449","date":"2023-08-12","proceeding":null,"authors":["Xiaoming Chen"],"abstract":"In this article, we introduce an instruction set architecture (ISA) for processing-in-memory (PIM) based deep neural network (DNN) accelerators. The proposed ISA is for DNN inference on PIM-based architectures. It is assumed that the weights have been trained and programmed into PIM-based DNN accelerators before inference, and they are fixed during inference. We do not restrict the devices of PIM-based DNN accelerators. Popular devices used to build PIM-based DNN accelerators include resistive random-access memory (RRAM), flash, ferroelectric field-effect transistor (FeFET), static random-access memory (SRAM), etc. The target DNNs include convolutional neural networks (CNNs) and multi-layer perceptrons (MLPs). The proposed ISA is transparent to both applications and hardware implementations. It enables to develop unified toolchains for PIM-based DNN accelerators and software stacks. For practical hardware that uses a different ISA, the generated instructions by unified toolchains can easily converted to the target ISA. The proposed ISA has been used in the open-source DNN compiler PIMCOMP-NN (https://github.com/sunxt99/PIMCOMP-NN) and the associated open-source simulator PIMSIM-NN (https://github.com/wangxy-2000/pimsim-nn).","url_abs":"https://arxiv.org/abs/2308.06449v1","url_pdf":"https://arxiv.org/pdf/2308.06449v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"instruction-set-architecture-isa-for","repo_url":"https://github.com/sunxt99/pimcomp-nn","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"instruction-set-architecture-isa-for","repo_url":"https://github.com/wangxy-2000/pimsim-nn","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}