The computing world faces a perplexing but exciting challenge. On one hand, we see the continued deceleration of Moore’s Law economics and scaling for conventional semiconductor devices threatening the familiar innovation cycle of faster, cheaper and cooler systems. On the other hand, new computation models, a tsunami of bigger, better data, progress on deep learning methods, advances in parallel architectures, and more intelligent “things" are poised to revolutionize software, systems and underlying hardware platforms dramatically and perhaps quickly.
This workshop focused on three themes, related to the scaling of computing to meet the opportunity:
- scaling of both devices and cloud to create deeper insights from bigger data,
- scaling of efficiency in energy, memory and cost to enable ubiquitous autonomous devices and cloud,
- development of new models of computation that exploit advances in machine learning, application-derived architecture insights and higher levels of representation.
| Technical Program | |||
|---|---|---|---|
| 9:00 | Welcome | Rick Bahr/ Chris Rowen | |
| 9:15 | Keynote: The End of Road for General Purpose Processors and the Future of Computing | Prof. John Hennessy (Stanford) | Member Content: PDF |
| Session: Scaling Devices & Cloud Systems for Bigger Data Chair: Dr. Chris Rowen |
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| 10:15 | From Embedded to Scalable: Challenges in the Development of Scalable Real Time System | Alan Gatherer (Huawei) | Member Content: PDF |
| 10:45 | Memory Hierarchy for Web Search | Grant Ayers (Stanford) | NA |
| 11:15 |
MacroBase: An Analytics Engine for Prioritizing Attention in Fast Data |
Prof. Peter Bailis (Stanford) | Member Content: PDF |
| Session: Scaling Efficiency Chair: Rick Bahr |
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| 1:00 | Spatial: a Language for Programming Configurable Accelerators | Prof. Kunle Olukotun (Stanford) | Member Content: PDF |
| 1:30 |
Silicon Photonics for 2.5D Interposers: Chip-Level Optical Communication for Manycore Processors |
Yvain Thonnart (CEA-Leti) | Member Content: PDF |
| 2:00 | Heterogeneous Integration of Nano-scale Fabrics: 1D, 2D and 3D | Prof. Eric Pop (Stanford) | Member Content: PDF |
| Session: New Computation Platforms and Models Chair: Prof. Subhasish Mitra (Stanford) |
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| 3:00 | Deep Learning Computing Needs for Autonomous Cars: Benchmarking and Optimizing | Unmesh Bordoloi (General Motors) | Member Content: PDF |
| 3:30 | Scaling Deep Learning to Thousands of Machines |
Ioannis Mitliagkas (Stanford PostDoc) |
Member Content: PDF |
| 4:00 |
Scaling ARM from One to One Trillion Cores |
Eric Van Hensbergen (ARM) | Member Content: PDF |
| 4:45 |
Panel Algorithms vs Architectures: Where's the big leverage in the deep learning era? (Moderator: Prof. Kunle Olukotun; Panelists: Marc Duranton (CEA LETI), Unmesh Bordoloi, Eric Van Hensbergen, Prof. John Hennessy) |
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