1. IBM Research Division © 2007 IBM Corporation July 22, 2008 The 50B Transistor Challenge Mikko Lipasti Department of Electrical and Computer Engineering University of Wisconsin - Madison IBM T.J. Watson Research Center July 22 and 23, 2008

2. IBM Research Division 50B Transistors on a Chip?  History –1997 IEEE Computer Special Issue, 1B T/chip by 2007 3 papers advocate single fast core – CMU, Michigan, Wisconsin IRAM – Berkeley RAW – MIT SMT – Washington Multicore – Stanford  11 years later, 50x more transistors –We still need faster cores : computation Fundamentally constrained by power –Will get more than one core : communication Need efficient interconnects and coherent caches –Will get lots of on-chip memory Need to think about new algorithms and new approaches to use it 2July 22, 2008

3. IBM Research Division (1) What Will We Do With 50B Transistors?  50B transistors/chip dramatically alters data centers  E.g. Nokia moving aggressively into services –Google, Yahoo, MSN each provision ~1M servers –Now provision for 10x installed base (phone vs. PC) Witness recent problems with Iphone/MobileMe  Impossible to anticipate applications –Youtube/Facebook/Flickr/Twitter –Unstructured real world data –Organize, search, extract semantic knowledge, mashups, …  Existing and future server apps all benefit 3July 22, 2008

4. IBM Research Division (2) How Will We Design Chips with 50B Transistors  Three things that processors need to be good at: –Computation –Communication –Storage/Memory  Focus on cost and nature of computation  Focus on cost of communication  Shift emphasis to memory 4July 22, 2008

5. IBM Research Division Cost of Computation  Less than 10% of energy spent on useful work –EPI overhead has gotten out of hand –Need to rethink operand delivery [ICCD’07], queues [ISPLED’07], caches, register files, control, …  Exploit program attributes –Solve hard problems via elimination Macro-ops : no single-cycle operations [MICRO’03, HPCA’06] –Do the hard parts with narrow values [JILP’07]  Eliminate redundancy, excessive pipelines –Clever clock gating [ISLPED’06, ICCD’07] –Remove renaming, register file, clocked scheduler, pipelines [submitted]  Goal: reduce EPI by 10x at fixed process technology and MIPS 5July 22, 2008

6. IBM Research Division Cost of Communication  Reduce coherence overhead and speculation –Region coherence [ISCA’05, ASPLOS’06, HPCA’08]  Exploit locality of communication patterns –Switched circuits [CALetters’07, NOCS’08] –On-chip multicasting [ISCA’08] –Multicast coherence [submitted]  New technologies –Nanophotonic rings [HP Labs collaboration] –Massive bandwidth, speed-of-light latency –Lots of interesting problems to solve 6July 22, 2008

7. IBM Research Division Emphasis on Memory  In future processes, memory will be easier than logic –Reliability, variability: well-known solutions (ECC, sparing) –Interesting new technologies (PCRAM, etc.) –Not caches -- diminishing returns  Return to more regular, “memory-like” devices and logic? –Gate array, LUT, PLA  Majority of 50B T must not be switching –Remembering is cheaper than computing Revisit value locality/reuse/memoization? –New search algorithms: TCAM accelerator [ICCD’08] : Logic in memory—but not IRAM! 7July 22, 2008

8. IBM Research Division Unstructured Real-World Data  Internet is exploding with data –Text –Semantic knowledge –Photo, video, audio  It is all in digital form but all we can do is view and copy it  Algorithms for analysis range from poor to nonexistent –Machine learning?  Why not learn from nature? 8July 22, 2008

9. IBM Research Division Brains  Human brain  Von Neumann machine –Face recognition: <500ms –Neurons are slow: Critical path is a handful of “gates” –Fundamentally different computational model  Made of shoddy, unreliable parts “…neurons are noisy, unreliable devices, … the nervous system averages over many cells to compensate for these shoddy components.” -Christof Koch  We can build it. We have the technology. Dec. 3, 2007MICRO’-40 Panel: Computing Beyond Von Neumann9

10. IBM Research Division Brains (2)  Human neocortex: –~20B neurons, ~200T synapses –Structurally homogenous –Hypothesis: runs common algorithm  Apply architecture 101? –Abstraction layers –Hierarchy and replication –Simulation/analysis/synthesis –Massively parallel fault-tolerant hardware  Best news: no need for parallel programming –Train vs. program –Let’s Build Brains! Dec. 3, 2007MICRO’-40 Panel: Computing Beyond Von Neumann10

11. IBM Research Division Summary  Computation : –Reduce cost (EPI) by 10x –New algorithms  Communication –Streamline coherence protocols, interconnects –Exploit new technologies  Storage/Memory –Reliability/variability –Logic in memory/new algorithms  Brain computing for unstructured real-world data 11July 22, 2008

12. IBM Research Division Questions? http://www.ece.wisc.edu/~pharm