R. Khaddam-Aljameh, M. Stanisavljevic, J. F. Mas, G. Karunaratne, M. Braendli, Femg Liu, Abhairaj Singh, S. M. Müller, U. Egger, A. Petropoulos, T. Antonakopoulos, K. Brew, Samuel Choi, I. Ok, F. Lie, N. Saulnier, V. Chan, I. Ahsan, V. Narayanan, S. Nandakumar, M. L. Gallo, P. Francese, A. Sebastian, E. Eleftheriou
{"title":"HERMES Core -基于14nm CMOS和pcm的内存计算核心,采用300ps/LSB线性化cco adc阵列和本地数字处理","authors":"R. Khaddam-Aljameh, M. Stanisavljevic, J. F. Mas, G. Karunaratne, M. Braendli, Femg Liu, Abhairaj Singh, S. M. Müller, U. Egger, A. Petropoulos, T. Antonakopoulos, K. Brew, Samuel Choi, I. Ok, F. Lie, N. Saulnier, V. Chan, I. Ahsan, V. Narayanan, S. Nandakumar, M. L. Gallo, P. Francese, A. Sebastian, E. Eleftheriou","doi":"10.23919/VLSICircuits52068.2021.9492362","DOIUrl":null,"url":null,"abstract":"We present a 256×256 in-memory compute (IMC) core designed and fabricated in 14nm CMOS with backend-integrated multi-level phase-change memory (PCM). It comprises 256 linearized current controlled oscillator (CCO)-based ADCs at a compact 4µm pitch and a local digital processing unit performing affine scaling and ReLU operations A novel frequency-linearization technique for CCOs is introduced, leading to accurate on-chip matrix-vector-multiply (MVM) when operating over 1 GHz. Measured classification accuracies on MNIST and CIFAR-10 datasets are presented when two cores are employed for deep learning (DL) inference The measured energy efficiency is 10.5 TOPS/W at a performance density of 1.59 TOPS/mm2.","PeriodicalId":106356,"journal":{"name":"2021 Symposium on VLSI Circuits","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"52","resultStr":"{\"title\":\"HERMES Core – A 14nm CMOS and PCM-based In-Memory Compute Core using an array of 300ps/LSB Linearized CCO-based ADCs and local digital processing\",\"authors\":\"R. Khaddam-Aljameh, M. Stanisavljevic, J. F. Mas, G. Karunaratne, M. Braendli, Femg Liu, Abhairaj Singh, S. M. Müller, U. Egger, A. Petropoulos, T. Antonakopoulos, K. Brew, Samuel Choi, I. Ok, F. Lie, N. Saulnier, V. Chan, I. Ahsan, V. Narayanan, S. Nandakumar, M. L. Gallo, P. Francese, A. Sebastian, E. Eleftheriou\",\"doi\":\"10.23919/VLSICircuits52068.2021.9492362\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a 256×256 in-memory compute (IMC) core designed and fabricated in 14nm CMOS with backend-integrated multi-level phase-change memory (PCM). It comprises 256 linearized current controlled oscillator (CCO)-based ADCs at a compact 4µm pitch and a local digital processing unit performing affine scaling and ReLU operations A novel frequency-linearization technique for CCOs is introduced, leading to accurate on-chip matrix-vector-multiply (MVM) when operating over 1 GHz. Measured classification accuracies on MNIST and CIFAR-10 datasets are presented when two cores are employed for deep learning (DL) inference The measured energy efficiency is 10.5 TOPS/W at a performance density of 1.59 TOPS/mm2.\",\"PeriodicalId\":106356,\"journal\":{\"name\":\"2021 Symposium on VLSI Circuits\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"52\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 Symposium on VLSI Circuits\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/VLSICircuits52068.2021.9492362\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Symposium on VLSI Circuits","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/VLSICircuits52068.2021.9492362","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
HERMES Core – A 14nm CMOS and PCM-based In-Memory Compute Core using an array of 300ps/LSB Linearized CCO-based ADCs and local digital processing
We present a 256×256 in-memory compute (IMC) core designed and fabricated in 14nm CMOS with backend-integrated multi-level phase-change memory (PCM). It comprises 256 linearized current controlled oscillator (CCO)-based ADCs at a compact 4µm pitch and a local digital processing unit performing affine scaling and ReLU operations A novel frequency-linearization technique for CCOs is introduced, leading to accurate on-chip matrix-vector-multiply (MVM) when operating over 1 GHz. Measured classification accuracies on MNIST and CIFAR-10 datasets are presented when two cores are employed for deep learning (DL) inference The measured energy efficiency is 10.5 TOPS/W at a performance density of 1.59 TOPS/mm2.