TY - GEN
T1 - Rebooting the data access hierarchy of computing systems
AU - Hwu, Wen Mei W.
AU - Hajj, Izzat El
AU - De Gonzalo, Simon Garcia
AU - Pearson, Carl
AU - Kim, Nam Sung
AU - Chen, Deming
AU - Xiong, Jinjun
AU - Sura, Zehra
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/11/28
Y1 - 2017/11/28
N2 - We have been experiencing two very important movements in computing. On the one hand, a tremendous amount of resource has been invested into innovative applications such as first-principle-based methods, deep learning and cognitive computing. On the other hand, the industry has been taking a technological path where application performance and energy efficiency vary by more than two orders of magnitude depending on their parallelism, heterogeneity, and locality. We envision that a “perfect storm” is coming because of the interaction between these two movements. Many of these new and high-valued applications need to touch a very large amount of data with little data reuse and data movement has become the dominating factor for both power and performance of these applications. It will be critical to match the compute throughput to the data access bandwidth and to locate the compute near data. Much has been and continuously needs to be learned about algorithms, languages, compilers and hardware architecture in this movement. What are the killer applications that may become the new driver for future technology development? How hard is it to program existing systems to address the data movement issues today? How will we program these systems in the future? How will innovations in memory devices present further opportunities and challenges in designing new systems? What is the impact on long-term software engineering cost of applications? In this paper, we present some lessons learned as we design the IBM-Illinois C3SR (Center for Cognitive Computing Systems Research) Erudite system inside this perfect storm.
AB - We have been experiencing two very important movements in computing. On the one hand, a tremendous amount of resource has been invested into innovative applications such as first-principle-based methods, deep learning and cognitive computing. On the other hand, the industry has been taking a technological path where application performance and energy efficiency vary by more than two orders of magnitude depending on their parallelism, heterogeneity, and locality. We envision that a “perfect storm” is coming because of the interaction between these two movements. Many of these new and high-valued applications need to touch a very large amount of data with little data reuse and data movement has become the dominating factor for both power and performance of these applications. It will be critical to match the compute throughput to the data access bandwidth and to locate the compute near data. Much has been and continuously needs to be learned about algorithms, languages, compilers and hardware architecture in this movement. What are the killer applications that may become the new driver for future technology development? How hard is it to program existing systems to address the data movement issues today? How will we program these systems in the future? How will innovations in memory devices present further opportunities and challenges in designing new systems? What is the impact on long-term software engineering cost of applications? In this paper, we present some lessons learned as we design the IBM-Illinois C3SR (Center for Cognitive Computing Systems Research) Erudite system inside this perfect storm.
KW - Big data
KW - Heterogeneous computing
KW - Low-complexity algorithms
KW - Memory bandwidth
KW - Throughput oriented computing
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U2 - 10.1109/ICRC.2017.8123667
DO - 10.1109/ICRC.2017.8123667
M3 - Conference contribution
AN - SCOPUS:85043526679
T3 - 2017 IEEE International Conference on Rebooting Computing, ICRC 2017 - Proceedings
SP - 1
EP - 4
BT - 2017 IEEE International Conference on Rebooting Computing, ICRC 2017 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE International Conference on Rebooting Computing, ICRC 2017
Y2 - 8 November 2017 through 9 November 2017
ER -