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Symmetric and CC-NUMA

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Symmetric and CC-NUMA Scope Design experiences of SMPs and Coherent Cache Nonuniform Memory Access (CC-NUMA) NUMA Natural extension of SMP systems Architectures ... – PowerPoint PPT presentation

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Title: Symmetric and CC-NUMA


1
Symmetric and CC-NUMA
2
Scope
  • Design experiences of SMPs and Coherent Cache
    Nonuniform Memory Access (CC-NUMA)
  • NUMA
  • Natural extension of SMP systems

3
Architectures
Shared Memory logic structure
SMP architecture
. . .
Node 1
Node N
4
Advantages of shard memory systems (SMP or
CC-NUMA)
  • Symmetry
  • Any processor can access any memory location and
    I/O device
  • Single address space
  • Single system image
  • One copy of OS, database app, etc
  • Reside in the shared memory
  • User no control over data distribution,
    redistribution
  • Single OS schedules processes
  • Easy workload management, dynamic load balancing

5
Advantages of shard memory systems (SMP or
CC-NUMA)
  • Caching
  • Data locality supported in the hierarchy
  • Coherency
  • Enforced by the hardware?
  • MESI-like snoopy protocol
  • Memory Communication
  • Low latency
  • Simple load/store instructions
  • Hardware generates coherency information

6
Basic Issues that SMPs must address
  • Availability
  • Biggest problem
  • Failure of the bus, memory, OS !!
  • Bottleneck
  • Compete for the memory bus and shard memory
  • Packet switched-bus (split transactions)
  • Latency
  • Low latency but still large compared to CPU
  • Memory bandwidth vs. Processor speed vs. Memory
    capacity
  • Scalability
  • A bus is not scalable

7
CC-NUMA
  • Extends SMPs by connecting several SMP nodes into
    a larger system
  • Employ directory based cache coherent protocol
  • While maintaining the advantages, attacks the
    scalability problem

8
Distributed shared memory enhances
  • Scalability
  • Memory capacity, I/O capabilities increase by
    adding more nodes
  • Bandwidth
  • An app can access multiple local memories
    concurrently
  • Availability
  • Multiple copies of a portion of OS can run on
    multiple nodes
  • Failure of one will not disrupt the entire system

9
Programming
  • We said that
  • data structures get distributed
  • Cache coherency then tracks the changes
  • Any issues? (remote cache vs local memory)
  • P, Q processes
  • A, B arrays
  • P Q
  • Phase 1 use(A) use(B)
  • Phase 2 use(B) use(A)
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