InOrder ToDo List

Python Configurability

• Resource Configuration - How can we specify what resources are instantiated via the Python config files?
  • ResourceType - Type of resource (Enum type)
    • ResourceParams - Parameters for this type of resource
    • Request - List of requests for this type of resource (Enum type)
      • Latency - operation latency and issue latency (intra/inter thread)
    • Count - Number of such resource type

• Pipeline Description
  • InstSchedule - Instruction schedule specified as a vector of InstClassSchedule
    • InstClassSchedule - Vector of schedules per instruction class - load/store, Int execute, FP execute, specialized inst, etc. (do we still want a distinction between front end and back end schedules?)
  • ResourceRequestList - Vector of ResourceRequest (per stage?)
    • ResourceRequest - Vector of requests for resources
  • ResourceType/Request options

• Multithreading Models?
  • None (single threaded)
  • Fine-grained (switch context every cycle or every few cycles, like Ultrasparc T2)
  • Coarse-grained (switch context on thread stalls, like 'SwitchOnCacheMiss' currently)
  • SMT (all contexts active, like 'SMT' currently)

Simulation Speed

• Instruction Schedule Work
  • Use Vector of Vectors instead of Priority Queue
  • Identify Instruction Schedule Types (via Tuple)
  • Cache Instruction Schedule, Generate On-Demand
  • Instructions walk through schedule by incrementing pointer instead of popping from queue
    • If dynamic schedule is needed, then copy the remaining part of schedule and let the instruction add/remove as it pleases
    • Can we cache dynamic schedules? Is there a better solution here?
• Event-Sleeping Work
  • Sleep instructions waiting for an long-delay event
  • Sleep CPU w/no activity (partially implemented)

ISA Support

• ALPHA - completed
• MIPS - completed
• X86 - not completed
• SPARC - not completed

Full System Support

• TBD

Checkpointing

• TBD

Regression Tests

TBD

*Move some of these to Flyspray?*