Proxics: an efficient programming model for far memory accelerators
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866908980010287104 |
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| author | Liu, Zikai Pressel, Niels Schult, Jasmin Meier, Roman Xu, Pengcheng Roscoe, Timothy |
| author_facet | Liu, Zikai Pressel, Niels Schult, Jasmin Meier, Roman Xu, Pengcheng Roscoe, Timothy |
| contents | The use of disaggregated or far memory systems such as CXL memory pools has renewed interest in Near-Data Processing (NDP): situating cores close to memory to reduce bandwidth requirements to and from the CPU. Hardware designs for such accelerators are appearing, but there lack clean, portable OS abstractions for programming them.
We propose a programming model for NDP devices based on familiar OS abstractions: virtual processors (processes) and inter-process communication channels (like Unix pipes).
While appealing from a user perspective, a naive implementation of such abstractions is inappropriate for NDP accelerators: the paucity of processing power in some hardware designs makes classical processes overly heavyweight, and IPC based on shared buffers makes no sense in a system designed to reduce memory bandwidth.
Accordingly, we show how to implement these abstractions in a lightweight and efficient manner by exploiting compilation and interconnect protocols. We demonstrate them with a real hardware platform runing applications with a range of memory access patterns, including bulk memory operations, in-memory databases and graph applications.
Crucially, we show not only the benefits over CPU-only implementations, but also the critical importance of efficient, low-latency communication channels between CPU and NDP accelerators, a feature largely neglected in existing proposals. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_18120 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Proxics: an efficient programming model for far memory accelerators Liu, Zikai Pressel, Niels Schult, Jasmin Meier, Roman Xu, Pengcheng Roscoe, Timothy Operating Systems Hardware Architecture Emerging Technologies Software Engineering The use of disaggregated or far memory systems such as CXL memory pools has renewed interest in Near-Data Processing (NDP): situating cores close to memory to reduce bandwidth requirements to and from the CPU. Hardware designs for such accelerators are appearing, but there lack clean, portable OS abstractions for programming them. We propose a programming model for NDP devices based on familiar OS abstractions: virtual processors (processes) and inter-process communication channels (like Unix pipes). While appealing from a user perspective, a naive implementation of such abstractions is inappropriate for NDP accelerators: the paucity of processing power in some hardware designs makes classical processes overly heavyweight, and IPC based on shared buffers makes no sense in a system designed to reduce memory bandwidth. Accordingly, we show how to implement these abstractions in a lightweight and efficient manner by exploiting compilation and interconnect protocols. We demonstrate them with a real hardware platform runing applications with a range of memory access patterns, including bulk memory operations, in-memory databases and graph applications. Crucially, we show not only the benefits over CPU-only implementations, but also the critical importance of efficient, low-latency communication channels between CPU and NDP accelerators, a feature largely neglected in existing proposals. |
| title | Proxics: an efficient programming model for far memory accelerators |
| topic | Operating Systems Hardware Architecture Emerging Technologies Software Engineering |
| url | https://arxiv.org/abs/2604.18120 |