Lune

HPCA2026Top-tier venue

Cohet: A CXL-Driven Coherent Heterogeneous Computing Framework with Hardware-Calibrated Full-System Simulation

Yanjing Wang, Lizhou Wu, Sunfeng Gao, Yibo Tang, Junhui Luo, Zicong Wang, Yang Ou, Dezun Dong, Nong Xiao, Mingche Lai

2026Year
1Citations
1Top-tier citations

Abstract

Conventional heterogeneous computing systems built on PCIe interconnects suffer from inefficient fine-grained host-device interactions and complex programming models. In recent years, many proprietary and open cache-coherent interconnect standards have emerged, among which compute express link (CXL) prevails in the open-standard domain after acquiring several competing solutions. Although CXL-based coherent heterogeneous computing holds the potential to fundamentally transform the collaborative computing mode of CPUs and XPUs, research in this direction remains hampered by the scarcity of available CXL-supported platforms, immature software/hardware ecosystems, and unclear application prospects. This paper presents Cohet, the first CXL-driven coherent heterogeneous computing framework. Cohet decouples the compute and memory resources to form unbiased CPU and XPU pools which share a single unified and coherent memory pool. It exposes a standard malloc/mmap interface to both CPU and XPU compute threads, which share a single per-process page table for user applications, leaving the OS dealing with smart memory allocation, page auto-migration, and management of heterogeneous resources. This design significantly simplifies heterogeneous parallel programming to a level comparable to homogeneous programming. To facilitate Cohet research, we also present a fullsystem cycle-level simulator named SimCXL, which is capable of modeling all CXL sub-protocols and device types. SimCXL has been rigorously calibrated against a real CXL testbed with various CXL memory and accelerators, showing an average simulation error of 3 %. Our evaluation reveals that CXL.cache reduces latency by 68 % and increases bandwidth by14.4×14.4 \timescompared to DMA transfers at cacheline granularity. Building upon these insights, we demonstrate the benefits of Cohet with two killer apps, which are remote atomic operation (RAO) and remote procedure call (RPC). Compared to PCIe-NIC design, CXL-NIC achieves a 5.5 to40.2×40.2 \timesspeedup for RAO offloading and an average speedup of1.86×\mathbf{1. 8 6} \timesforRPC\mathbf{R P C}(de)serialization offloading.

Ask about this paper

Your agent reads all of it.

Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.

Questions to start from

Your agent calls

Luneget_paper_fulltext

Ask in Lune

Free to start. No credit card required.

lune papers fulltext ecbd76d9-07df-43b0-a53f-733c4a555dad

Cited by top-tier papers1

Ask how each one uses it

Builds on38

Related papers

Dusk over the sea between two cliffs drawn in fine vertical lines