Simplepim: A software framework for productive and efficient processing-in-memory
Data movement between memory and processors is a major bottleneck in modern
computing systems. The processing-in-memory (PIM) paradigm aims to alleviate this …
computing systems. The processing-in-memory (PIM) paradigm aims to alleviate this …
SwiftRL: Towards Efficient Reinforcement Learning on Real Processing-In-Memory Systems
Reinforcement Learning (RL) trains agents to learn optimal behavior by maximizing reward
signals from experience datasets. However, RL training often faces memory limitations …
signals from experience datasets. However, RL training often faces memory limitations …
Analysis of Distributed Optimization Algorithms on a Real Processing-In-Memory System
S Rhyner, H Luo, J Gómez-Luna, M Sadrosadati… - arXiv preprint arXiv …, 2024 - arxiv.org
Machine Learning (ML) training on large-scale datasets is a very expensive and time-
consuming workload. Processor-centric architectures (eg, CPU, GPU) commonly used for …
consuming workload. Processor-centric architectures (eg, CPU, GPU) commonly used for …
PimPam: Efficient Graph Pattern Matching on Real Processing-in-Memory Hardware
Graph pattern matching is powerful and widely applicable to many application domains.
Despite the recent algorithm advances, matching patterns in large-scale real-world graphs …
Despite the recent algorithm advances, matching patterns in large-scale real-world graphs …