Arjun Suresh S7, R College of Engineering Trivandrum

MEMS-based storage Relational database layout FRM (Flexible Retrieval Model) Query Processing on FRM Evaluation Conclusion Outline

Building Storage on MEMS MEMS are Micro Electrical Mechanical Systems.  Basic functions: sensors and actuators  Built by standard silicon processing  Combine mechanical and electrical components  Enable “systems-on-a-chip”

Why need MEMS-based storage?  Huge gaps between disks and RAM 1000,000 latency gap (10ms vs 50 ns), widening 50% yearly price gap per byte 1000 life gap  MEMS narrows gaps 10X smaller latency than disk 100X cheaper than RAM in the range 1 – 10 GB 100 MB - 1 GB/s bandwidth 10 GB capacity with a penny size  Desired for energy and volume critical systems

EEPROM/Flash DRAM Hard Disk Latency Cost per Byte MEMS-based Storage Technology Trends

Using pits in the polymers made by tip heating to store data IBM Millipede

MEMS Storage Architecture Read/write tips Read/write tips Media Bits stored underneath each tip Bits stored underneath each tip side view

MEMS Storage Architecture Media Sled X Y

Springs MEMS Storage Architecture

Anchors attach the springs to the chip. Anchors attach the springs to the chip. Anchor X Y MEMS Storage Architecture

Sled is free to move Sled is free to move X Y MEMS Storage Architecture

Sled is free to move Sled is free to move X Y MEMS Storage Architecture

Springs pull sled toward center Springs pull sled toward center X Y MEMS Storage Architecture

X Y Springs pull sled toward center Springs pull sled toward center MEMS Storage Architecture

Actuators pull sled in both dimensions Actuators pull sled in both dimensions Actuator X Y MEMS Storage Architecture

Actuators pull sled in both dimensions Actuators pull sled in both dimensions X Y MEMS Storage Architecture

Actuators pull sled in both dimensions Actuators pull sled in both dimensions X Y MEMS Storage Architecture

Actuators pull sled in both dimensions Actuators pull sled in both dimensions X Y MEMS Storage Architecture

Actuators pull sled in both dimensions Actuators pull sled in both dimensions X Y MEMS Storage Architecture

Probe tips are fixed Probe tips are fixed Probe tip X Y MEMS Storage Architecture

X Y Probe tips are fixed Probe tips are fixed MEMS Storage Architecture

X Y Sled only moves over the area of a single rectangle Sled only moves over the area of a single rectangle One probe tip per rectangle One probe tip per rectangle Each tip accesses data at the same relative position Each tip accesses data at the same relative position MEMS Storage Architecture

Properties of MEMS Storage Sweep area of One probe tip

Properties of MEMS Storage N bits M bits One tip region One tip sector

Physical Parameters Number of tips6400 Max number of active tips1280 Tip sector size8 bytes Bits per tip region2000X2000 X axis settle time0.125ms Average turnaround time0.06ms

Existing Work on Integration of MEMS Storage Solution proposed by CMU researchers Mapping MEMS storage into conventional disk Adapt I/O scheduling and data placement to MEMS Preliminary study shows Reduce the I/O stall times by 4 to 74 times over disks Improve the overall application run times by 1.9 to 4.4 Reduce the energy consumption by times

Better solutions?? The approach of mapping MEMS into disk Simplify the procedure of integration of MEMS Does not consider the physical properties of MEMS

Relational Data Placement StudentGrade recordID name char(16) perm ID int(8) age int(8) grade int(8) record1Mary record2John record3Bob record4Jane

N-ary Storage Model (NSM) Store records in a relation in slotted disk pages Organize records sequentially on the disk pages Page HeaderMary John Bob Jane P4P3P2p1

Decomposition Storage Model(DSM) Divide a relation into sub-relations based on the number of attributes Each sub-relation corresponds to each attribute Each sub-relation is organized into pages in the same way as NSM Page Header1Mary2 John3Bob4Jane P4P3P2P1 Page Header P4P3P2P1 Page Header P4P3P2P1 Page Header P4P3P2P1 grade nameperm ID age A disk page

Partition Attributes Across (PAX) Within each page, PAX groups all values of each attribute into a mini-page A page is divided into mini-pages based on the number of attributes It stores the same data as NSM in each page Page HeaderMaryJohn BobJane P4P3P2P P4P3P2P P4P3P2P P4P3P2P1 A disk page

Common Workload Requirements Relational data should be compatible with OLTP workloads Due to the update characteristics, relations need to be accessed in a row-wise manner OLAP workloads Only a subset of attributes is of interest, data placement should facilitate data retrieval on a column-wise fashion

Flexible Retrieval Model (FRM) Facilitates data retrieval in both row-wise and column-wise manner Retrieves the relevant subsets of the relations Uses two dimensional layout of MEMS storage Improves the I/O utilization Maximize the concurrent tips to only retrieve the necessary data It is also cache-friendly Use intra-record locality

FRM Data Placement and Retrieval Given a relation with three attributes, the size of each attribute is 8 bytes Placing this relation in 4x4 MEMS-based storage 4 concurrent tips (0, 0) (0, 1) (0, 0) (0, 1) Attr1 Attr2 Attr3 (0, 0) (0, 1) (0, 2) (1, 2)

Query Processing on FRM Selection and projection without index Two-dimensional table scan Selection and projection with index Encode data position as 4-tuple (tip-x, tip-y, offset-x, offset-y) Joins Index-based or hash

Experiment Setup MEMS storage: 1280 concurrent tips out of 6400 total tips Pentium II Celeron 433X2 processors L1 cache:16KB, 32-byte cache line, 20 ns delay L2 cache:128KB, 32-byte cache line, 200 ns delay A relation R with 1.28 million records Sixteen 8-byte attributes in each record Queries: SELECT A 1, A 2, …, A n FROM R WHERE A 1 > Bound;

Memory utilization The selected attributes in queries Consumed memory(MB)

I/O performance NSM and PAX have the same I/O time I/O time of FRM is proportional to the size of retrieved attributes

Selection Queries (2 attributes) Cache Utilization

Selection Queries (13 attributes)

Projection Queries Selectivity = 50%

Projection Queries Selectivity =10%

Conclusion and Future Work Proposed a relational data placement scheme for MEMS-based storage Take advantage of two-dimensional MEMS access feature Arrange MEMS rows and columns to relational attributes and records Save IO cost and improve cache performance Other cache friendly techniques for MEMS- based storage devices are to be explored

Thank You……