CPU Design · All levels
Integer ALU Pipelines
Execution Units & Pipelines: ALU depth, forwarding network reach, and issue balance determine integer latency and throughput; poor bypass planning turns short dependencies into frequent structural stalls.
What this topic teaches
Integer ALU Pipelines turns CPU design theory into actionable review decisions. ALU depth, forwarding network reach, and issue balance determine integer latency and throughput; poor bypass planning turns short dependencies into frequent structural stalls. The target is evidence-backed closure, not opinion-driven tuning.
Senior-engineer framing question
When integer pipeline utilization, bypass hazard frequency, and single-cycle ALU throughput shifts, can you prove first failing stage, dominant mechanism, accountable owner, and release-safe mitigation?
CPU PIPELINE VIEW - Integer ALU Pipelines
fetch -> decode -> rename -> dispatch -> execute -> retire
| | | | | |
icache uop flow map table queueing FU ports ROB commit
steady-state goal:
keep every stage supplied without bubbles or flush storms
Focus: connect metric movement to the first stage loss
Metric tracked: integer pipeline utilization, bypass hazard frequency, and single-cycle ALU throughputArchitecture visuals
Draw the mechanism before changing knobs. These visuals are optimized for design reviews and interview whiteboards.
Integer dependency spacing
CPU PIPELINE VIEW - Integer ALU Pipelines
fetch -> decode -> rename -> dispatch -> execute -> retire
| | | | | |
icache uop flow map table queueing FU ports ROB commit
steady-state goal:
keep every stage supplied without bubbles or flush storms
Focus: identify bypass depth and hazard windows in ALU-heavy code
Metric tracked: integer pipeline utilization, bypass hazard frequency, and single-cycle ALU throughputALU port binding in OoO core
OOO CORE BLOCK DIAGRAM - Integer ALU Pipelines
decode -> rename -> dispatch -> reservation stations -> execute units
| | |
free-list / map table wakeup-select writeback
\ | /
+-------- reorder buffer / retire ---------+
Focus: show how scheduler decisions map integer uops to execution portsOut-of-order control map
OOO CORE BLOCK DIAGRAM - Integer ALU Pipelines
decode -> rename -> dispatch -> reservation stations -> execute units
| | |
free-list / map table wakeup-select writeback
\ | /
+-------- reorder buffer / retire ---------+
Focus: rename to retire dataflowMemory hierarchy map
CPU CACHE + MEMORY HIERARCHY - Integer ALU Pipelines
[ L1I ] [ L1D ]
32-64KB, ~4 cycles
\ /
[ L2 ]
512KB-2MB, ~12 cycles
|
[ L3 ]
shared LLC, 30-60 cycles
|
[ DDR/HBM memory ]
80-150ns effective
Optimization lens: latency vs capacity tradeoffSpeculation lens
BRANCH PREDICTOR VIEW - Integer ALU Pipelines
fetch PC -> BTB lookup -> direction predictor -> target select -> fetch redirect
| | |
BTB miss cost confidence RAS / indirect path
branch resolves in execute:
correct prediction -> pipeline keeps flowing
mispredict -> flush + restart + refill
Focus: minimize wrong-path workOwnership layers
CPU OWNERSHIP LAYERS - Integer ALU Pipelines
artifact area owner
---------------- ----------------------------
architecture integer datapath owner
RTL/microarch physical design owner
software/tools compiler scheduling owner
Rule: every regressed metric must map to an explicit owner and closure artifact.Evidence required
Primary metric: integer pipeline utilization, bypass hazard frequency, and single-cycle ALU throughput.
Primary artifact: ALU stage timing chart, forwarding conflict report, and integer mix profile.
Owners to include: integer datapath owner, physical design owner, compiler scheduling owner.
One reproducible failing workload and one stable comparator run.
One run with fully locked environment metadata for causal comparison.
Compute-memory limit lens
CPU ROOFLINE - Integer ALU Pipelines
performance
^
| compute roof
| /
| /
|--------------/---------------- memory roof
+----------------------------------------------> arithmetic intensity
memory-bound compute-bound
Interpretation: separate compute and memory limitsKey takeaways
Classify stage loss before proposing fixes.
Use artifacts to separate mechanism from symptoms.
Close with owner accountability and rollback criteria.
Common pitfalls
Using average IPC alone while ignoring tail behavior.
Comparing traces across mismatched binaries or thermal states.
Calling closure without workload-level validation.
CPU deep dive
Execution throughput depends on port balance, bypass quality, and realistic instruction mix assumptions.
Concept diagram
EXECUTION DATAPATH
issue -> ALU/FPU/vector/LSQ ports -> writeback -> retireMetric graph
EXECUTION LOSS DRIVERS
port conflicts █████
bypass hazards ████
LSQ ordering stalls ███Reports and artifacts
port pressure heatmap
pipeline hazard report
ALU/FPU/vector utilization split
LSQ ordering diagnostics
Mini case study
A compiler scheduling update over-concentrated uops on one port class, reducing effective multi-issue throughput.
Debug branches
Map instruction classes to port availability
Validate forwarding depth against dependency chains
Inspect LSQ ordering events before widening pipes
Senior review question
Ask: which CPI/latency evidence proves this topic is truly closed beyond synthetic benchmarks?
Key takeaways
Always connect microarchitectural counter changes to product workload outcomes.
Lock binary, compiler, firmware, and thermal metadata before comparing CPU traces.
Common pitfalls
Treating average IPC as sufficient proof while ignoring latency tails and outliers.
Applying predictor or prefetch tweaks without first-failing-stage attribution.
Declaring closure without reproducible perf, correctness, and power gates.