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Pipeline Performance and CPI Decomposition: Worked Example

Worked Example for Pipeline Performance and CPI Decomposition.

Worked example

Worked Example for Pipeline Performance and CPI Decomposition is anchored on Measured CPI broken into ideal base CPI, structural stalls, data stalls, control stalls, and memory wait contributions.. Convert observations into mechanism-backed decisions with explicit ownership.

A regression flags Measured CPI broken into ideal base CPI, structural stalls, data stalls, control stalls, and memory wait contributions.. Strong closure isolates first failing mechanism, proves causality, applies one bounded change, and validates blast radius.

System view

diagram
RISC-V PIPELINE DIAGRAM - Pipeline Performance and CPI Decomposition

PC -> IF -> ID -> EX -> MEM -> WB
      |     |      |      |      |
  i-cache decode  ALU/BR  LSU    regfile write
              \   |
               +-> branch resolve + redirect

Hot paths:
  - branch + load-use dependencies in ID/EX
  - memory latency stretching MEM stage
  - writeback arbitration for integer/vector units

Focus: keep control hazards predictable

Evidence matrix

diagram
RISC-V EVIDENCE MATRIX - Pipeline Performance and CPI Decomposition

+--------------------------+--------------------------------+--------------------------------+---------------------------+
| Evidence                 | Tells you                      | Does not prove                 | Next action               |
+--------------------------+--------------------------------+--------------------------------+---------------------------+
| perf counter timeline    | where regression appears       | exact mechanism causality      | correlate with trace      |
| decode/control dump      | control intent per instruction | pipeline side-effect ordering  | inspect retire semantics  |
| trap + CSR logs          | privilege/fault behavior       | performance bottleneck alone   | pair with CPI buckets     |
| MMU/TLB walk trace       | translation behavior           | full system QoS impact         | test mixed workloads      |
| post-fix trend graph     | movement after fix             | long-term stability            | run stress matrix         |
+--------------------------+--------------------------------+--------------------------------+---------------------------+
  1. Capture baseline and failing traces under fixed metadata tags.

  2. Classify stage loss and dominant mechanism.

  3. Collect CPI accounting workbook and counter-instrumentation plan with benchmark-by-benchmark bottleneck attribution..

  4. Apply one bounded fix with owner signoff.

  5. Run validation matrix and decide ship/rollback.