TY - GEN
T1 - CHIME
T2 - 35th IEEE International Conference on Application-Specific Systems, Architectures and Processors, ASAP 2024
AU - Gajaria, Dhruv
AU - Adegbija, Tosiron
AU - Gomez, Kevin
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Processing-in-cache (PiC) and Processing-in-memory (PiM) architectures, especially those utilizing bit-line computing, offer promising solutions to mitigate data movement bottlenecks within the memory hierarchy. While previous studies have explored the integration of compute units within individual memory levels, the complexity and potential overheads associated with these designs have often limited their capabilities. This paper introduces a novel PiC/PiM architecture, Concurrent Hierarchical In-Memory Processing (CHIME), which strategically incorporates heterogeneous compute unitsacross multiple levels of the memory hierarchy. This design targets the efficient execution of diverse, domain-specific workloads by placing computations closest to the data where it optimizes performance, energy consumption, data movement costs, and area. CHIME employs STT-RAM due to its various advantages in PiC/PiM computing, such as high density, low leakage, and better resiliency to data corruption from activating multiple word lines. We demonstrate that CHIME enhances concurrency and improves compute unit utilization at each level of the memory hierarchy. We present strategies for exploring the design space, grouping, and placing the compute units across the memory hierarchy. Experiments reveal that, compared to the state-of-the-art bit-line computing approaches, CHIME achieves significant speedup and energy savings of 57.95% and 78.23% for various domain-specific workloads, while reducing the overheads associated with single-level compute designs.
AB - Processing-in-cache (PiC) and Processing-in-memory (PiM) architectures, especially those utilizing bit-line computing, offer promising solutions to mitigate data movement bottlenecks within the memory hierarchy. While previous studies have explored the integration of compute units within individual memory levels, the complexity and potential overheads associated with these designs have often limited their capabilities. This paper introduces a novel PiC/PiM architecture, Concurrent Hierarchical In-Memory Processing (CHIME), which strategically incorporates heterogeneous compute unitsacross multiple levels of the memory hierarchy. This design targets the efficient execution of diverse, domain-specific workloads by placing computations closest to the data where it optimizes performance, energy consumption, data movement costs, and area. CHIME employs STT-RAM due to its various advantages in PiC/PiM computing, such as high density, low leakage, and better resiliency to data corruption from activating multiple word lines. We demonstrate that CHIME enhances concurrency and improves compute unit utilization at each level of the memory hierarchy. We present strategies for exploring the design space, grouping, and placing the compute units across the memory hierarchy. Experiments reveal that, compared to the state-of-the-art bit-line computing approaches, CHIME achieves significant speedup and energy savings of 57.95% and 78.23% for various domain-specific workloads, while reducing the overheads associated with single-level compute designs.
KW - concurrency
KW - domain-specific computing
KW - hierarchical computing
KW - Processing-in-cache (PiC)
KW - Processing-in-memory (PiM)
KW - STT-RAMs
UR - http://www.scopus.com/inward/record.url?scp=85203109505&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85203109505&partnerID=8YFLogxK
U2 - 10.1109/ASAP61560.2024.00053
DO - 10.1109/ASAP61560.2024.00053
M3 - Conference contribution
AN - SCOPUS:85203109505
T3 - Proceedings of the International Conference on Application-Specific Systems, Architectures and Processors
SP - 228
EP - 236
BT - Proceedings - 2024 IEEE 35th International Conference on Application-Specific Systems, Architectures and Processors, ASAP 2024
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 24 July 2024 through 26 July 2024
ER -