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arXiv:1911.11313cs.DC

Summarizing CPU and GPU Design Trends with Product Data

Yifan Sun, Nicolas Bohm Agostini, Shi Dong, David Kaeli

Abstract

Moore's Law and Dennard Scaling have guided the semiconductor industry for the past few decades. Recently, both laws have faced validity challenges as transistor sizes approach the practical limits of physics. We are interested in testing the validity of these laws and reflect on the reasons responsible. In this work, we collect data of more than 4000 publicly-available CPU and GPU products. We find that transistor scaling remains critical in keeping the laws valid. However, architectural solutions have become increasingly important and will play a larger role in the future. We observe that GPUs consistently deliver higher performance than CPUs. GPU performance continues to rise because of increases in GPU frequency, improvements in the thermal design power (TDP), and growth in die size. But we also see the ratio of GPU to CPU performance moving closer to parity, thanks to new SIMD extensions on CPUs and increased CPU core counts.

arXiv comments
Fix flops/watt error
Journal reference
DOI
Subjects
cs.DCDistributed, Parallel, and Cluster Computing

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  1. The singularity is close? 1 comment
    • No. You can't easily equate human intelligence to required processing power but I've seen estimates of 10^15 to 10^18 FLOPS [1]. There's a huge variance there. Now consider the cost per FLOPS [2] and the energy cost of that [3]. Capital costs are still huge but let's focus on…

      jmyeetView on HNParent context

    • Not sure what “tame” means in this context. Performance per watt has been increasing every year for a long time and continues to do so [1]. So temperature is really just a design choice. One example, pick a performance get a power. Once you have a power, pick the mechanical…

      egsmiView on HNParent context

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