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CS 294-42: Technology Trends. September 12, 2011. Ion Stoica (http://www.cs.berkeley.edu/~istoica/classes/cs294/11/). “Skate where the puck's going, not where it's been” – Walter Gretzky. Processors. - PowerPoint PPT Presentation
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CS 294-42: Technology Trends
Ion Stoica (http://www.cs.berkeley.edu/~istoica/classes/cs294/11/)
September 12, 2011
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“Skate where the puck's going, not where it's been” – Walter Gretzky
Processors
MIMD (Multi-Core Processors) – linear increase: two additional cores every two years
SIMD (GPUs) – exponential increase: width double every four years
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SSDs Performance:
Reads: 25us latency Write: 200us latency Erase: 1,5 ms
Steady state, when SSD full One erase every 64 or 128 reads (depending on page
size) Lifetime: 100,000-1 million writes per page
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Rule of thumb: writes 10x more expensive than reads, and erases 10x more expensive than writes
Storage Performance & PriceBwdth (sequential R/W)
Cost/GB Size
HHD 50-100 MB/s $0.05-0.1/GB 2-4 TB
SSD1 200-500 MB/s (SATA)1.5 GB/s (PCI)
$2-4/GB 200GB-1TB
DRAM 10-16 GB/s $12-13/GB 64GB-256GB
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Bwdth: SSD up to x10 than HDD, DRAM > x10 than SSDPrice: HDD x20 less than SSD, SSD x5 less than DRAM
1http://www.fastestssd.com/featured/ssd-rankings-the-fastest-solid-state-drives/
Storage Price Trends RAMs: x2 every ~20 month (http://www.jcmit.com/memoryprice.htm)
1990-2000: x75 decrease 2000-2010: x63 decrease
Disks: x2 decrease every ~2 years SSDs prices dropped faster than disk prices for
last 5 year(http://rogerluethy.wordpress.com/2010/12/07/price-trends-of-hdds-vs-ssds/) But decrease slightly less over last year
6Storage price halves every ~2 years
Hard Drives (25 years ago) IBM Personal Computer/AT (1986)
30 MB hard disk - $500 30-40ms seek time 0.7-1 MB/s (est.)
730-40sec to scan entire disk
Memory (today)
96 GB RAM - $650-800 (ECC RAM) Memory bus speed: 10-16 GB/s
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6-10sec to scan entire memory!
Working Set: RAM Doubling Software (1995)
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Working Set (Today)
When was the last time your experience trashing on your laptop?
Memory growing faster than application’s needs – conjecture
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Today’s memory, yesterday’s disk!
Working Set – Datacenters % of jobs whose full inputs fit in memory (~1 week)
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Memory (GB)
Facebook (% jobs)
Microsoft (% jobs)
Yahoo! (% jobs)
8 69 38 66
16 74 51 81
32 96 82 97.5
64 97 98 99.5
128 98.8 99.4 99.8
192 99.5 100 100
256 99.6 100 100Nearly all jobs’ inputs fitting in main memory in near future?
(Ganesh Ananthanarayanan)
(Random) Thoughts Today’s disks, yesterday’s tapes [John Ousterhout]
Today’s memory, yesterday’s disk? Or should be today’s SSDs, yesterday’s disks? SSDs not great for caches (due limited writes) Perfect for archival though and GFS-like filer systems ;-)
In-memory computation not enough for interactive workloads Parallelism only way out if need to touch a lot of data
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(Random) Thoughts (cont’d) Today’s servers in Hadoop clusters: 10-12 disks
Up to 1GB/s bwdth How to take advantage of this?
GPU use will only increase: faster increase in processing power than CPUs Need better support for virtualization What to do about memory bwdth?
For data intensive apps, locality will continue to be critical
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Predictions??
Memory the new disk Working sets of more and more apps will fit in memory
SSDs will become the new tape (archival)
GPUs: main driver for increasing processing power Will be integrated in the main processor
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