buzzword
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buzzword [2014/03/28 17:39] rachata |
buzzword [2014/04/02 18:13] rachata |
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| ===== Lecture 23 (3/28 Fri.) ===== | ===== Lecture 23 (3/28 Fri.) ===== | ||
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| * DRAM design choices | * DRAM design choices | ||
| * Cost/density/latency/BW/Yield | * Cost/density/latency/BW/Yield | ||
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| * TL-DRAM vs. DRAM cache (adding a small cache in DRAM) | * TL-DRAM vs. DRAM cache (adding a small cache in DRAM) | ||
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| + | | ||
| + | ===== Lecture 24 (3/31 Mon.) ===== | ||
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| + | * Memory controller | ||
| + | * Different commands | ||
| + | * Memory scheduler | ||
| + | * Determine the order of requests to be issued to DRAM | ||
| + | * Age/hit-miss status/types(load/store/prefetch/from GPU/from CPU)/criticality | ||
| + | * Row buffer | ||
| + | * hit/conflict | ||
| + | * open/closed row | ||
| + | * Open row policy | ||
| + | * Closed row policy | ||
| + | * Tradeoffs between open and closed row policy | ||
| + | * What if the programs has high row buffer locality: open row might benefit more | ||
| + | * Closed row will service misses request faster | ||
| + | * Bank conflict | ||
| + | * Interference from different applications/threads | ||
| + | * Differnt programs/processes/threads interfere with each other | ||
| + | * introduce more row buffer/bank conflicts | ||
| + | * Memory schedule has to manage these interference | ||
| + | * Memory hog problems | ||
| + | * Interference in the data/command bus | ||
| + | * FR-FCFS | ||
| + | * Why does FR-FCFS make sense? | ||
| + | * Row buffer has lower lantecy | ||
| + | * Issues with FR-FCFS | ||
| + | * Unfairness | ||
| + | * STFM | ||
| + | * Fairness issue in memory scheduling | ||
| + | * How does STFM calculate the fairness and slowdown | ||
| + | * How to estimate slowdown time when it is runing alone | ||
| + | * Definition of fairness (based on STFM, different papers/areas define fairness differently) | ||
| + | * PAR-BS | ||
| + | * Parallelism in programs | ||
| + | * Intereference across banks | ||
| + | * How to form a batch | ||
| + | * How to determine ranking between batches/within a batch | ||
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| + | ===== Lecture 25 (2/2 Wed.) ===== | ||
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| + | * Latency sensitivity | ||
| + | * Performance drops a lot when the memory request latency is long | ||
| + | * TCM | ||
| + | * Tradeoff between throughput and fairness | ||
| + | * Latency sensitive cluster (non-intensive cluster) | ||
| + | * Ranking based on memory intensity | ||
| + | * Bandwidth intensive cluster | ||
| + | * Round robin within the cluster | ||
| + | * Generally latency sensitive cluster has more priority | ||
| + | * Provide robust fairness vs. throughput | ||
| + | * Complexity of TCM? | ||
| + | * Different ways to control interference in DRAM | ||
| + | * Partitioning of resource | ||
| + | * Channel partitioning: map applications that interfere with each other in a different channel | ||
| + | * Keep track of application's characteristics | ||
| + | * Dedicate a channel might waste the bandwidth | ||
| + | * Need OS support to determine the channel bits | ||
| + | * Source throttling | ||
| + | * A controller throttle the core depends on the performance target | ||
| + | * Example: Fairness via source throttling | ||
| + | * Detect unfairness and throttle application that is interfering | ||
| + | * How do you estimate slowdown? | ||
| + | * Threshold based solution: hard to configure | ||
| + | * App/thread scheduling | ||
| + | * Critical threads usually stall the progress | ||
| + | * Designing DRAM controller | ||
| + | * Has to handle the normal DRAM operations | ||
| + | * Read/write/refresh/all the timing constraints | ||
| + | * Keep track of resources | ||
| + | * Assign priorities to different requests | ||
| + | * Manage requests to banks | ||
| + | * Self-optimizing controller | ||
| + | * Use machine learning to improve DRAM controller | ||
| + | * DRAM Refresh | ||
| + | * Why does DRAM has to refresh every 64ms | ||
| + | * Banks are unavailable during refresh | ||
| + | * LPDDR mitigate this by using a per-bank refresh | ||
| + | * Has to spend longer time with bigger DRAM | ||
| + | * Distributed refresh: stagger refresh every 64 ms in a distributed manner | ||
| + | * As oppose to burst refresh (long pause time) | ||
| + | * RAIDR: Reduce DRAM refresh by profiling and binning | ||
| + | * Some row do not have to be refresh very frequently | ||
| + | * Profile the row | ||
| + | * High temperature changes the retention time: need online profiling | ||
| + | * Bloom filter | ||
| + | * Represent set membership | ||
| + | * Approximated | ||
| + | * Can contain false positive | ||
| + | * Better/more hash function helps eliminate this | ||
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buzzword.txt · Last modified: 2015/04/27 18:20 by rachata
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