AIM: Energy-Efficient Aggregation Inside the Memory Hierarchy

作者：Ahn Junwhan^*; Yoo Sungjoo; Choi Kiyoung

来源：ACM Transactions on Architecture and Code Optimization, 2016, 13(4): 34.

DOI：10.1145/2994149

• Processing-in-memory
• near-data processing
• aggregation
• locality-adaptive execution

In this article, we propose Aggregation-in-Memory (AIM), a new processing-in-memory system designed for energy efficiency and near-term adoption. In order to efficiently perform aggregation, we implement simple aggregation operations in main memory and develop a locality-adaptive host architecture for inmemory aggregation, called cache-conscious aggregation. Through this, AIM executes aggregation at the most energy-efficient location among all levels of the memory hierarchy. Moreover, AIM minimally changes existing sequential programming models and provides fully automated compiler toolchain, thereby allowing unmodified legacy software to use AIM. Evaluations show that AIM greatly improves the energy efficiency of main memory and the system performance.

• 出版日期2016-12