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User Level Interprocess Communication for Shared Memory Multiprocessor by Bershad, B.N. Anderson, A.E., Lazowska, E.D., and Levy, H.M. Introduction. RPC Help in implementing distributed applications by eliminating the need to implement communication mechanism.

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User Level Interprocess Communication for Shared Memory Multiprocessorby Bershad, B.N. Anderson, A.E., Lazowska, E.D., and Levy, H.M.

introduction
Introduction
  • RPC
    • Help in implementing distributed applications by eliminating the need to implement communication mechanism.
    • Decomposed system provides advantages of failure isolation, extensibility and modularity. So RPC is used even when the call is in the same machine.
introduction1
Introduction
  • RPC Costs
    • Stub overhead
    • Message buffer overhead (4 copies)
    • Access validation
    • Message transfer
    • Scheduling
    • Context switch
    • Dispatch
introduction2
Introduction
  • LRPC Costs
    • Stub overhead
    • Message buffer overhead (1 copy)
    • Only necessary access validation
    • Message transfer
    • Only necessary scheduling
    • Context switch is minimized by using domain caching
introduction3
Introduction
  • IPC
    • Main components (All work in Kernel)
      • Processor reallocation (process context switch)
      • Data transfer
      • Thread management
    • Problems
      • Processor reallocation is expensive
      • Parallel applications need user-level thread management
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URPC
  • User-Level Remote Procedure Call
    • Shared memory multiprocessors
      • Processor reallocation - minimize
      • Data transfer - user-level (Package called URPC)
      • Thread management - user-level (Package called FastThreads)
processor reallocation
Processor Reallocation
  • Limit the frequency of processor reallocation
    • Why
      • Cost of process context switch is more expensive than thread context switch
      • Cost of invoking kernel
  • Client makes procedure call in server address space
  • Invoke kernel
  • Kernel reallocates processor to server address space
  • Server finishes the job
  • Invoke kernel
  • Kernel reallocates processor to client address space
  • Client resumes the work
processor reallocation1
Processor Reallocation
  • Limit the frequency of processor reallocation
    • How
      • Optimistic reallocation policy
        • Client has other works
        • Server has or will soon has a processor to do the job
    • Uniprocessor can delay processor reallocation
  • Client makes procedure call in server address space
  • Client does something else
  • Server finishes the job
  • Client resumes the work
processor reallocation2
Processor Reallocation
  • Problems
    • Inappropriate situations
      • Single-threaded client, real time applications & high-latency I/O applications
      • Solve: Allow client to force processor reallocation
    • Underpowered
      • No processor to handle the pending request from client
      • Solve: Donate – idle processor donates itself to underpowered address space
processor reallocation3
Processor Reallocation
  • Problems
    • Voluntary return of processor
      • Processor working in server never return to client because it is too busy working on the request of other clients.
      • Solve: enforce the process reallocation when necessary such as high priority waiting while low priority job is running and processor is idling
processor reallocation4
Processor Reallocation
  • LRPC VS URPC
    • Domain caching looks for idle processor in server context
    • Optimistic reallocation assume there will be an available processor in server context and queue the request to be done later
    • URPC needs two level scheduling decisions including looking for idle processor and underpoweredaddress space while LRPC does not.
data transfer
Data Transfer
  • Use pair-wise shared memory to avoid the need of copying in kernel.
  • Both give the same level of security since data need to be passed into stubs before it can be used
thread management
Thread Management
  • Arguments
    • Fine-grained parallel application needs high performance thread management which could only be achieved by implementing in user-level
    • Communication & Thread management can achieve very good performances when both are implemented at user-level
thread management1
Thread Management
  • Features of kernel such as time slicing degrade performance of applications
  • To invoke thread management operation, kernel traps are required
  • Thread management policy implemented in kernel is unlikely to be efficient for all parallel applications
thread management2
Thread Management
  • Threads block in order to
    • Synchronize their activities in same address space
    • Wait for external events from different address space
      • Communication implemented at kernel level will result in synchronization at both user level and kernel level
performance
Performance
  • Thread managementfaster at user level
  • Component breakdown
performance1
Performance
  • Call latency & throughput is at worst when S=0
conclusion
Conclusion
  • Moving the possible functionality from kernel into user-lever to improve performance
  • In order to achieve great performance on multiprocessors, system need to be designed to support its functionality
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