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Divisible Load Scheduling

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A computational & networkable load that is arbitrarily partitionable (divisible) ... Linear and Deterministic Modeling. Tractable Recursive/Linear Equation Solution ... – PowerPoint PPT presentation

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Title: Divisible Load Scheduling


1
Divisible Load Scheduling
  • A Tutorial

Thomas Robertazzi University at Stony Brook
2
What is a Divisible Load?
  • A computational networkable load that is
    arbitrarily partitionable (divisible) amongst
    processors and links.
  • There are no precedence relations.

3
Simple Application Example
  • Problem Sum 1000 trillion numbers
  • Approach Partition the numbers among 100
    processors
  • But how?

4
Simple Application Example
  • To optimize solution time (maximize speedup) one
    needs to take into account heterogeneous link and
    processor speeds, computation and communication
    intensities, interconnection topology and
    scheduling policy.
  • Divisible Load Scheduling Theory Can Do This!

5
Applications (Generic)
  • Grid Computing/Meta-computing
  • Data Intensive Computing
  • Sensor Processing
  • Image Processing
  • Scientific/Engineering Computing
  • Financial Computing

6
Applications (Specific)
  • Pattern Searching
  • Database Computation
  • Matrix-Vector Computation
  • EM Field Calculation (CAD)
  • Edge Detection

7
DLT Modeling Advantages
  • Linear and Deterministic Modeling
  • Tractable Recursive/Linear Equation Solution
  • Schematic Language
  • Equivalent Elements
  • Many Applications

8
Interconnection Topologies
  • Linear Daisy Chain
  • Bus
  • Single Level and Multilevel Trees
  • Mesh
  • Hypercube

9
Directions Scalability
1
1
3
1
2
1
Simultaneous Distribution (Scalable)
Sequential Distribution (Saturation)
Hung Robertazzi
Cheng Robertazzi
10
An Example
  • Model Specifications
  • A star network( single level tree network), and
    multi-level tree.
  • Computation and transmission time is a linear
    function of the size of load.
  • Level to Level Store and Forward Switching
  • Same Level Concurrent Load Distribution.

11
  • Children without Front End
  • After receiving the assigned data, each child
    proceeds to process the data.

12
  • Timing Diagram (single level tree)
  • Children without Front End

13
m1 unknows vs. m1 Eqs.
  • Recursive equations
  • Normalization equation

14
  • Distribution Solution

15
  • The load distribution solution is similar to the
    solution of the state-dependent M/M/1 queuing
    system.

16
Similarities to Queueing Theory
  • Linear model and tractable solutions
  • Schematic Language
  • Equivalent Elelements
  • Infinite Size Networks

17
  • Speedup Analysis

18
  • Speedup Analysis (continued)

19
  • Tree Network
  • (Children without Front Ends)

20
Collapsing single level trees
21
Bandwidth of Fat Tree
  • Definition The bandwidth of level j in a fat
    tree can be defined as pj-1z.

22
Directions Sequencing and Installments
  • Daisy Chain Surprise
  • Efficiency Rule

Ghose, Mani Bharadwaj
23
Directions Sequencing and Installments
  • Multi-installment for Sequential Distribution

6
4
5
3
1
2
Ghose, Mani Bharadwaj
24
Directions Sequencing and Installments
Diminishing returns in using multi-installment
distribution.
Ghose, Mani Bharadwaj
25
Directions Sequencing and Installments
Drozdowski
26
Directions Time Varying Modeling
Sohn Robertazzi
Can be solved with integral calculus.
27
Directions Monetary Cost Optimization
N
  • Min CTotal S ancnwnTcp

n1
Bus
Processors
Optimal Sequential Distribution if
cn-1wn-1 less than cnwn for all n
Sohn, Luryi Robertazzi
28
Directions Monetary Cost Optimization
  • 2 US Patents
  • Patent 5,889,989 (1999) Processor Cost
  • Patent 6,370,560 (2001) Processor and

  • Link Cost
  • Enabling technology for an open e-commerce
  • market in leased proprietary computing.

Sohn, Charcranoon, Luryi Robertazzi
29
Directions Database Modeling
Expected time to find multiple records in flat
file database
Ko Robertazzi
30
Directions Realism
  • Finite Buffers (Bharadwaj)
  • Job Granularity (Bharadwaj)
  • Queueing Model Integration

31
Directions Experimental Work
Database Join (Drozdowski)
32
Directions Future Research
  • Operating Systems
  • Incorporate divisible load scheduling
  • into (distributed) operating systems
  • Measurement Process Modeling
  • Integrate measurement process
  • modeling into divisible scheduling

33
Directions Future Research
  • Pipelining (Dutot)
  • Concept Distribute load to
  • further processors first
    for
  • speedup improvement
  • Improvement reported for daisy chains

34
Directions Future Research
  • System Parameter Estimation (Ghose)
  • Concept Send small probing loads across
  • links and to processors
    to estimate
  • available effort
  • Challenge Rapid change in link processor
  • state

35
DLT has a Good Future
  • Many Applications including
  • wireless sensor networks
  • Tractable (Modeling Computation)
  • Rich Theoretical Basis

36
Thank you!
  • Questions???
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