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Course contents

  • Architecture Metrics Reference
  • Workload Taxonomy for Architects
  • Architecture Glossary
  • Computer Architecture Cheatsheet
  • Pipeline Fundamentals14
    • Pipeline Throughput
      • The Five-Stage Datapath
      • Stage Depth and Clock Period
      • CPI and Speedup Arithmetic
      • Hazard Classes: Structural, Data and Control
      • Forwarding and Stalls
    • Branch Prediction and Fetch
    • Out-of-Order Superscalar Execution
  • Memory Hierarchy15
  • NoC and Interconnect Architecture6
  • Coherency and Memory Ordering9
  • Performance Analysis9
  • Accelerator Architectures6
  • SoC Architecture Tradeoffs9
  • Architecture Interview Prep14
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‹Pipeline Throughput
  1. Topics
  2. Computer Architecture
  3. Pipeline Fundamentals
  4. Pipeline Throughput
  5. Stage Depth and Clock Period

Computer Architecture · All levels

Stage Depth and Clock Period

How stage count sets clock period and why latency in nanoseconds grows while frequency rises.

On this page

    Splitting delay across stages

    Uncut logic with total delay D needs a period near D plus register overhead. Cut into S balanced stages, the period falls toward D/S plus one register delay.

    The slowest stage sets the clock. Uneven stages waste the gain, so balance matters more than count.

    Tclk​≈SD​+treg​f=Tclk​1​latency=S⋅Tclk​

    Frequency rises, time latency too

    Each added stage rank adds area, power and clock load. Latency in cycles grows by construction, and latency in nanoseconds grows slightly from register overhead.

    Stages S

    Clock period (D = 6 ns, t_reg = 0.3 ns)

    Frequency

    Latency

    1

    6.3 ns

    159 MHz

    6.3 ns

    2

    3.3 ns

    303 MHz

    6.6 ns

    3

    2.3 ns

    435 MHz

    6.9 ns

    6

    1.3 ns

    769 MHz

    7.8 ns

    Diagram
    Tclk = D / S + t_reg, with D = 6.0 ns and t_reg = 0.3 ns
    S = 1:  6.0 / 1 + 0.3 = 6.3 ns  ->  f = 1 / 6.3 ns = 159 MHz,  latency = 1 x 6.3 = 6.3 ns
    S = 2:  6.0 / 2 + 0.3 = 3.3 ns  ->  f = 1 / 3.3 ns = 303 MHz,  latency = 2 x 3.3 = 6.6 ns
    S = 3:  6.0 / 3 + 0.3 = 2.3 ns  ->  f = 1 / 2.3 ns = 435 MHz,  latency = 3 x 2.3 = 6.9 ns
    S = 6:  6.0 / 6 + 0.3 = 1.3 ns  ->  f = 1 / 1.3 ns = 769 MHz,  latency = 6 x 1.3 = 7.8 ns

    Pipelining raises throughput for streams of items. It does not hide latency: each item still takes S cycles, and feedback loops feel every added cycle.

    Where deeper stops paying

    Deeper stages expose more bubbles on every stall and lengthen branch recovery. Fetch bandwidth and hazard control must be rebalanced with each split.

    Extra flops add clock power with no work attached. A split needs an IPC-times-frequency gain at fixed power, shown in the next lesson.

    Common pitfall

    Declaring success from a frequency gain without checking retired instructions per cycle repeats the classic error. The worked 7 percent example in the next lesson lands near break-even.

    Interview

    Likely probe: how to decide whether a deeper pipeline is better. Compare IPC times frequency at fixed power, then inspect CPI components for branch and dependency penalties that ate the gain.

    Check yourself Logic with D = 4.8 ns and t_reg = 0.2 ns is split into 4 equal stages. What are the period, rate and latency?

    T = 4.8/4 + 0.2 = 1.4 ns, so about 714 MHz. Latency = 4 x 1.4 = 5.6 ns, longer than the unpipelined 5.0 ns but with about 3.6 times the results per ns (the ideal 4x minus register overhead).

    Check yourself One stage holds twice the delay of the others. What sets the clock, and what is the fix?

    The slow stage sets the clock for all stages. The fix is rebalancing work across the boundary, not adding more stages.

    Related topics

    • Pipelining

    • Performance method

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    See also

    • Hazard Classes: Structural, Data and Control
    • Forwarding and Stalls