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An evolving index of research papers and books I've read, with my notes on what matters and why.

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Compute-in-Memory1Datacenter Computing3Digital CIM1Processor1

Recently Reviewed

  • A 16nm 72kb 120.5TFLOPS/W Versatile-Format Dual-Representation Gain-Cell CIM Macro for General Purpose AI Tasks

    J-C. Tien et. al. — National Tsing Hua University and TSMC in Hsinchu, Taiwan

    Quality: Good

    A reconfigurable 2’s-complement and sign-magnitude scheme integrated within a versatile-format CIM macro supporting MX, LNS, FP, and INT for MAC operations.
    Stats: 16nm 72kb gain-cell array, energy efficiency of 120.5TFLOPS/W and throughput density of 3.18 TOPS/mm2 in MXINT8 mode.

    IEEE International Solid-State Circuits Conference (ISSCC) (2026)

  • Amdahl's law for tail latency
    Source

    Christina Delimitrou and Christos Kozyrakis — Stanford University

    Queueing theoretic models can guide design trade-offs in systems targeting tail latency, not just average performance.

    Communications of the ACM (2018)

  • The tail at scale
    Source

    Jeffrey Dean and Luiz André Barroso — Google

    Quality: Must Read

    Software techniques that tolerate latency variability are vital to building responsive large-scale web services.

    Communications of the ACM (2013)