TY - JOUR
T1 - Planting Fast-Growing Forest by Leveraging the Asymmetric Read/Write Latency of NVRAM-Based Systems
AU - Liang, Yu Pei
AU - Chen, Tseng Yi
AU - Chang, Yuan Hao
AU - Huang, Yi Da
AU - Shih, Wei Kuan
N1 - Publisher Copyright:
© 1982-2012 IEEE.
PY - 2022/10/1
Y1 - 2022/10/1
N2 - Owing to the considerations of cell density and low static power consumption, nonvolatile random-access memory (NVRAM) has been a promising candidate for collaborating with a dynamic random-access memory (DRAM) as the main memory in modern computer systems. As NVRAM also brings technical challenges (e.g., limited endurance and high writing cost) to computer system developers, the concept of write reduction becomes the famous doctrine in NVRAM-based system design. Unfortunately, a well-known machine learning algorithm, random forest, will generate a massive amount of write traffic to the main memory space during its construction phase. In other words, a random forest hits the Achilles' heel of NVRAM-based systems. For remedying this pain, our work proposes an NVRAM-friendly random forest algorithm, namely, Amine, for an NVRAM-based system. The design principle of Amine is to replace write operations with read accesses without raising the read complexity of the random forest algorithm. According to experimental results, Amine can effectively decrease the latency of random forest construction by 64%, compared with the original random forest algorithm.
AB - Owing to the considerations of cell density and low static power consumption, nonvolatile random-access memory (NVRAM) has been a promising candidate for collaborating with a dynamic random-access memory (DRAM) as the main memory in modern computer systems. As NVRAM also brings technical challenges (e.g., limited endurance and high writing cost) to computer system developers, the concept of write reduction becomes the famous doctrine in NVRAM-based system design. Unfortunately, a well-known machine learning algorithm, random forest, will generate a massive amount of write traffic to the main memory space during its construction phase. In other words, a random forest hits the Achilles' heel of NVRAM-based systems. For remedying this pain, our work proposes an NVRAM-friendly random forest algorithm, namely, Amine, for an NVRAM-based system. The design principle of Amine is to replace write operations with read accesses without raising the read complexity of the random forest algorithm. According to experimental results, Amine can effectively decrease the latency of random forest construction by 64%, compared with the original random forest algorithm.
KW - Decision tree
KW - nonvolatile memory
KW - nonvolatile random-access memory (NVRAM)-based learning
KW - random forest
UR - http://www.scopus.com/inward/record.url?scp=85119012838&partnerID=8YFLogxK
U2 - 10.1109/TCAD.2021.3126680
DO - 10.1109/TCAD.2021.3126680
M3 - 期刊論文
AN - SCOPUS:85119012838
SN - 0278-0070
VL - 41
SP - 3304
EP - 3317
JO - IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
JF - IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
IS - 10
ER -