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Course contents

  • Architecture Metrics Reference
  • Workload Taxonomy for Architects
  • Architecture Glossary
  • Computer Architecture Cheatsheet
  • Pipeline Fundamentals14
  • Memory Hierarchy15
  • NoC and Interconnect Architecture6
  • Coherency and Memory Ordering9
  • Performance Analysis9
  • Accelerator Architectures6
    • Accelerators for the Architect
      • When an Accelerator Pays Off
      • Dataflow Patterns as Reuse Contracts
      • Systolic Execution and Utilization Cliffs
      • Locality, Scratchpads and Tile Sizing
      • DMA and Double Buffering
      • Integration, Launch Cost and Signoff
  • SoC Architecture Tradeoffs9
  • Architecture Interview Prep14
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‹Accelerators for the Architect
  1. Topics
  2. Computer Architecture
  3. Accelerator Architectures
  4. Accelerators for the Architect
  5. Locality, Scratchpads and Tile Sizing

Computer Architecture · All levels

Locality, Scratchpads and Tile Sizing

Bytes per operation, scratchpads and tile sizing that keep traffic and energy in budget.

On this page

    Bytes per operation

    One MAC touches three 1 B operands, so zero reuse costs 3 B per MAC. Reuse divides the traffic of the reused tensor.

    Hit rate alone can lie. Bytes per operation at each level is the KPI, paired with energy.

    Diagram
    no reuse: 3 operands x 1 B = 3 B per MAC
    16x16 output tile: one weight serves 256 outputs -> 1 / 256 B per MAC ≈ 0.0039 B per MAC
    AMAT example: 1 + 0.05 x 20 = 1 + 1.0 = 2.0 cycles

    Scratchpads and tile fit

    A scratchpad holds exactly what the compiler placed. A cache guesses, which helps irregular code and hurts determinism.

    Assume 32 KiB of SRAM with double buffering. Each buffer holds 16 KiB, so a tile must fit 16 KiB.

    INT8 tile

    Bytes

    Double-buffered share of 32 KiB

    128x128

    16384 (16 KiB)

    32768 / 32768 = 100%, no headroom

    64x64

    4096 (4 KiB)

    8192 / 32768 = 25%

    Off-chip cost

    Off-chip movement sets energy and sustained bandwidth. Row-buffer hits, read-write turnaround and concurrency headroom decide what survives.

    Compression stays out of this topic. It is listed in legacy plans without traffic math, so no claim is made here.

    Report

    What it measures

    Bytes per op by level

    Traffic per useful MAC at SRAM, NoC and DRAM

    Bank conflict profile

    Serialization from strided tile layouts

    DRAM efficiency trend

    Row-hit rate and sustained versus peak bandwidth

    Common mistakes

    Common pitfall

    Celebrating a higher SRAM hit rate while DRAM bytes stay flat repeats the documented trap. Coherency and burst waste can eat the whole win.

    Interview

    Likely probes: the locality KPI and tile math.

    • Quote bytes per operation by level, never hit rate alone.

    • Fit tiles as 2x tile bytes within SRAM for double buffering.

    • Align strides to banks and bursts, or price the conflict.

    Check yourself SRAM hit rate rose but DRAM traffic did not fall. What failed?

    The locality assumption. Coherency traffic, burst waste or spill still dominates end to end.

    Check yourself SRAM is 32 KiB double-buffered. What is the largest square INT8 tile per buffer?

    128x128 at 16384 B, exactly one 16 KiB buffer.

    Related topics

    • Caches

    • Memory bandwidth and latency

    • DRAM Memory

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    See also

    • When an Accelerator Pays Off
    • Dataflow Patterns as Reuse Contracts
    • Integration, Launch Cost and Signoff