Översikt

  • Here are some recent studies on the topics relevant to seminar topics and some suggested conferences/journals: papers and tutorials from ISSCC-2020/2021, JSSC, TCAS etc are preffered.

    1.  S. Xie, C. Ni, A. Sayal, P. Jain, F. Hamzaoglu and J. P. Kulkarni, "16.2 eDRAM-CIM: Compute-In-Memory Design with Reconfigurable Embedded-Dynamic-Memory Array Realizing Adaptive Data Converters and Charge-Domain Computing," 2021 IEEE International Solid- State Circuits Conference (ISSCC), 2021, pp. 248-250, doi: 10.1109/ISSCC42613.2021.9365932.

    2. J. -W. Su et al., "16.3 A 28nm 384kb 6T-SRAM Computation-in-Memory Macro with 8b Precision for AI Edge Chips," 2021 IEEE International Solid- State Circuits Conference (ISSCC), 2021, pp. 250-252, doi: 10.1109/ISSCC42613.2021.9365984.

    3. Y. -D. Chih et al., "16.4 An 89TOPS/W and 16.3TOPS/mm2 All-Digital SRAM-Based Full-Precision Compute-In Memory Macro in 22nm for Machine-Learning Edge Applications," 2021 IEEE International Solid- State Circuits Conference (ISSCC), 2021, pp. 252-254, doi: 10.1109/ISSCC42613.2021.9365766.

    4. X. Si et al., "15.5 A 28nm 64Kb 6T SRAM Computing-in-Memory Macro with 8b MAC Operation for AI Edge Chips," 2020 IEEE International Solid- State Circuits Conference - (ISSCC), 2020, pp. 246-248, doi: 10.1109/ISSCC19947.2020.9062995.

    5. H. Jia et al., "15.1 A Programmable Neural-Network Inference Accelerator Based on Scalable In-Memory Computing," 2021 IEEE International Solid- State Circuits Conference (ISSCC), 2021, pp. 236-238, doi: 10.1109/ISSCC42613.2021.9365788.

    6. Z. Chen, X. Chen and J. Gu, "15.3 A 65nm 3T Dynamic Analog RAM-Based Computing-in-Memory Macro and CNN Accelerator with Retention Enhancement, Adaptive Analog Sparsity and 44TOPS/W System Energy Efficiency," 2021 IEEE International Solid- State Circuits Conference (ISSCC), 2021, pp. 240-242, doi: 10.1109/ISSCC42613.2021.9366045.

    7. R. Khaddam-Aljameh, P. -A. Francese, L. Benini and E. Eleftheriou, "An SRAM-Based Multibit In-Memory Matrix-Vector Multiplier With a Precision That Scales Linearly in Area, Time, and Power," in IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 29, no. 2, pp. 372-385, Feb. 2021, doi: 10.1109/TVLSI.2020.3037871.