Summarizing CPU and GPU Design Trends with Product Data
FOS: Computer and information sciences
Computer Science - Distributed, Parallel, and Cluster Computing
0103 physical sciences
Distributed, Parallel, and Cluster Computing (cs.DC)
01 natural sciences
DOI:
10.48550/arxiv.1911.11313
Publication Date:
2019-01-01
AUTHORS (4)
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.<br/>Fix flops/watt error<br/>
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