TPNM: A CXL Based General Purpose Tiered Process Near Memory Framework
Pingyi Huo, Anusha Devulapally, Hasan Al Maruf, Meena Arunachalam, Mahmut Kandemir, Vijaykrishnan Narayanan · 2025
Near-Memory Processing (NMP) has gained significant attention for its potential to accelerate various workloads. However, NMP performance suffers from challenges related to data locality and scalability, particularly in disaggregated datacenter environments. To address these issues, this paper presents TPNM (Tiered Processing Near Memory), a novel framework for near-data processing in disaggregated memory settings. TPNM leverages Compute Express Link (CXL) technology to enable processing both within memory devices and at the fabric switch level, creating a tiered approach to data processing. Evaluations across diverse workloads demonstrate significant performance improvements over baseline and existing near-data processing approaches. In particular, TPNM reduces latency by up to 4.76x compared to CPU-only baselines and by as much as 62 % compared to existing NMP-based solutions.