Program |
|
9.00 | Opening and Coffee |
9.15 |
Prof. Guang R. Gao MICRO 50 Years: a Personal Reflection on Dataflow Models of Computation |
10.00 |
Dr. Kemal Ebcioglu On the Future Evolution of Application-specific Supercomputers in the Cloud |
10.45 | Break |
11.00 |
Prof. Alex Shafarenko AstraKahn: Refining Applied Kahn's Networks |
11.45 | Lunch Break |
01.00 |
Prof. Sally A. McKee Some Like it Cold: Initial Testing Results for Cryogenic Computing Components |
01.45 |
Prof. Vladimir Lazarov |
02.30 |
Prof. Nader Bagherzadeh An overview of two of our efforts related to machine learning |
03.15 | Afternoon Coffee |
03.30 |
WG 10.3 Business |
05.00 | Closing |
06.30 |
Dinner at Lefteris Gyro restaurant in Mt Kisco, NY |
Prof. Guang R. Gao: MICRO 50 Years: a Personal Reflection on Dataflow Models of Computation
This talk starts with a personal reflection at the historical event of MICRO-50 anniversary as the 2017 recipient of Bob Ramakrishna Rau Award. The speaker provides a review on the legacy of Bob Rau’s contribution as well as personal interaction with Bob --- both have produced lasting impact in his own career on compiler and microarchitecture technology in the past 30 years. Facing the challenges of the end of Moore’s Law, as well as the challenges from applications in advanced data analytics and machine learning the speaker believes that it may be the time to initiate a new forum encouraging broader participation and direct interaction of scientists and engineers working on microarchitectures, compilers, hardware synthesis, runtime systems, and OS as a co-design community. He hopes that IFIP 10.3 Working Group on Concurrent Systems should be an excellent forum to start this interaction and conversation.
The speaker stresses that it is his personally view that 2017 Bob Rau Award is beyond himself – it is also a recognition of the seminal contribution and impact of the dataflow model of computation pioneered by Jack B. Dennis and Arvind at MIT - both are his mentors as the first Ph.D recipient of Computer Science at MIT from the People’s Republic of China since 1980.
Dr. Kemal Ebcioglu: On the Future Evolution of Application-specific Supercomputers in the Cloud
In this talk, we will describe a vision for next generation, easy-to-create, power efficient, custom hardware-accelerated cloud computing data centers with exascale computation capabilities in both technical and non-technical applications.
In our approach, high productivity in application-specific cloud hardware design is achieved by our C++ compiler technology which, unlike today's C-to-gates compilers, creates from general, ordinary single-threaded code (without specifying hardware structure) a customized supercomputer hardware system partitioned into multiple chips, where custom hardware components are interconnected by a plurality of lightweight scalable networks, instead of ordinary wires. Application memory is partitioned using compiler dependence analysis, removing the need for maintaining coherence between memory partitions, thus reducing hardware complexity and improving power efficiency. Furthermore, highly-parallel pre-emptive scheduling for sharing custom hardware resources in an application-specific cloud data center is done entirely by hardware.
Prof. Nader Bagherzadeh: An overview of two of our efforts related to machine learning
We are working on heterogeneous device mapping of neural networks
utilizing Tensorflow. By using genetic algorithms for the search space
and machine learning algorithm to predict the makespan of the neural
network. In another more low level hardware optimization work, we are
using approximate log multiplier to make CNN computations more energy
efficient.