4.1 22nm Next-generation IBM System z microprocessor-Reference-Cited by-同舟云学术

4.1 22nm Next-generation IBM System z microprocessor

Published:2015-02 Issue: Volume: Page:
ISSN:
Container-title:2015 IEEE International Solid-State Circuits Conference - (ISSCC) Digest of Technical Papers
language:
Short-container-title:

Author:

Warnock James,Curran Brian,Badar John,Fredeman Gregory,Plass Donald,Chan Yuen,Carey Sean,Salem Gerard,Schroeder Friedrich,Malgioglio Frank,Mayer Guenter,Berry Christopher,Wood Michael,Chan Yiu-Hing,Mayo Mark,Isakson John,Nagarajan Charudhattan,Werner Tobias,Sigal Leon,Nigaglioni Ricardo,Cichanowski Mark,Zitz Jeffrey,Ziegler Matthew,Bronson Tim,Strevig Gerald,Dreps Daniel,Puri Ruchir,Malone Douglas,Wendel Dieter,Mak Pak-Kin,Blake Michael

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/7054075/7062838/07062930.pdf?arnumber=7062930

Cited by 9 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. At the Locus of Performance: Quantifying the Effects of Copious 3D-Stacked Cache on HPC Workloads;ACM Transactions on Architecture and Code Optimization;2023-12-14

2. HyGain: High-performance, Energy-efficient Hybrid Gain Cell-based Cache Hierarchy;ACM Transactions on Architecture and Code Optimization;2023-03

3. The Interplay of Online and Offline Machine Learning for Design Flow Tuning;Machine Learning Applications in Electronic Design Automation;2022

4. Heterogeneity aware power abstractions for dynamic power dominated FinFET‐based microprocessors;IET Computers & Digital Techniques;2019-09-04

5. SynTunSys: A Synthesis Parameter Autotuning System for Optimizing High-Performance Processors;Machine Learning in VLSI Computer-Aided Design;2019