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Optimizing NUCA Organizations and Wiring Alternatives for Large Caches with CACTI 6.0

Published: 01 December 2007 Publication History

Abstract

A significant part of future microprocessor real estate will be dedicated to L2 or L3 caches. These on-chip caches will heavily impact processor perfor- mance, power dissipation, and thermal management strategies. There are a number of interconnect design considerations that influence power/performance/area characteristics of large caches, such as wire mod- els (width/spacing/repeaters), signaling strategy (RC/differential/transmission), router design, etc. Yet, to date, there exists no analytical tool that takes all of these parameters into account to carry out a design space exploration for large caches and estimate an optimal organization. In this work, we implement two major extensions to the CACTI cache modeling tool that focus on interconnect design for a large cache. First, we add the ability to model different types of wires, such as RC-based wires with different power/delay characteristics and differential low-swing buses. Second, we add the ability to model Non-uniform Cache Access (NUCA). We not only adopt state-of-the-art design space exploration strategies for NUCA, we also enhance this exploration by considering on-chip network contention and a wider spectrum of wiring and routing choices. We present a validation analysis of the new tool (to be released as CACTI 6.0) and present a case study to showcase how the tool can improve architecture research methodologies. Keywords: cache models, non-uniform cache archi- tectures (NUCA), memory hierarchies, on-chip intercon- nects.

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          cover image ACM Conferences
          MICRO 40: Proceedings of the 40th Annual IEEE/ACM International Symposium on Microarchitecture
          December 2007
          435 pages
          ISBN:0769530478

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          IEEE Computer Society

          United States

          Publication History

          Published: 01 December 2007

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          MICRO 40 Paper Acceptance Rate 35 of 166 submissions, 21%;
          Overall Acceptance Rate 484 of 2,242 submissions, 22%

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          Cited By

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          • (2024)SilvanForge: A Schedule-Guided Retargetable Compiler for Decision Tree InferenceProceedings of the ACM SIGOPS 30th Symposium on Operating Systems Principles10.1145/3694715.3695958(488-504)Online publication date: 4-Nov-2024
          • (2024)Control Flow Divergence Optimization by Exploiting Tensor CoresProceedings of the 61st ACM/IEEE Design Automation Conference10.1145/3649329.3658462(1-6)Online publication date: 23-Jun-2024
          • (2024)ngAP: Non-blocking Large-scale Automata Processing on GPUsProceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 110.1145/3617232.3624848(268-285)Online publication date: 27-Apr-2024
          • (2024)Enhancing Performance through Control-Flow Unmerging and Loop Unrolling on GPUsProceedings of the 2024 IEEE/ACM International Symposium on Code Generation and Optimization10.1109/CGO57630.2024.10444819(106-118)Online publication date: 2-Mar-2024
          • (2024)SIMILMicroprocessors & Microsystems10.1016/j.micpro.2024.105105111:COnline publication date: 1-Nov-2024
          • (2023)Reprogrammable non-linear circuits using ReRAM for NN acceleratorsACM Transactions on Reconfigurable Technology and Systems10.1145/3617894Online publication date: 10-Oct-2023
          • (2023)NAS-SE: Designing A Highly-Efficient In-Situ Neural Architecture Search Engine for Large-Scale Deployment56th Annual IEEE/ACM International Symposium on Microarchitecture10.1145/3613424.3614265(756-768)Online publication date: 28-Oct-2023
          • (2023)Grape: Practical and Efficient Graphed Execution for Dynamic Deep Neural Networks on GPUsProceedings of the 56th Annual IEEE/ACM International Symposium on Microarchitecture10.1145/3613424.3614248(1364-1380)Online publication date: 28-Oct-2023
          • (2023)Predictable GPU Wavefront Splitting for Safety-Critical SystemsACM Transactions on Embedded Computing Systems10.1145/360910222:5s(1-25)Online publication date: 31-Oct-2023
          • (2023)Paella: Low-latency Model Serving with Software-defined GPU SchedulingProceedings of the 29th Symposium on Operating Systems Principles10.1145/3600006.3613163(595-610)Online publication date: 23-Oct-2023
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