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ORCID35th Hot Chips Symposium 2023: Palo Alto, CA, USA
- 35th IEEE Hot Chips Symposium, HCS 2023, Palo Alto, CA, USA, August 27-29, 2023. IEEE 2023, ISBN 979-8-3503-3907-9
- Norman P. Jouppi, Andy Swing:
A Machine Learning Supercomputer with an Optically Reconfigurable Interconnect and Embeddings Support. 1-24 - Guiming Shi
, Yi Li, Xueqiang Wang, Zhanhong Tan, Dapeng Cao, Jingwei Cai, Yuchen Wei, Zehua Li, Wuke Zhang, Yifu Wu, Wei Xu, Kaisheng Ma:
PHEP: Paillier Homomorphic Encryption Processors for Privacy-Preserving Applications in Cloud Computing. 1-20 - Seungjae Moon, Junsoo Kim, Jung-Hoon Kim, Junseo Cha, Gyubin Choi, Seongmin Hong, Joo-Young Kim:
HyperAccel Latency Processing Unit (LPUTM) Accelerating Hyperscale Models for Generative AI. 1 - Chris Gianos:
Architecting for Flexibility and Value with Next Gen Intel® Xeon® Processors. 1-15 - Efraim Rotem:
Intel® Energy Efficiency Architecture. 1-17 - Felicia Guo, Nayiri Krzysztofowicz, Alex Moreno, Jeffrey Ni, Daniel Lovell, Yufeng Chi, Kareem Ahmad, Sherwin Afshar, Josh Alexander, Dylan Brater, Cheng Cao, Daniel Fan, Ryan Lund, Jackson Paddock, Griffin Prechter, Troy Sheldon, Shreesha Sreedhara, Anson Tsai, Eric Wu, Kerry Yu, Daniel Fritchman, Aviral Pandey, Ali Niknejad, Kristofer S. J. Pister, Borivoje Nikolic:
A Heterogeneous SoC for Bluetooth LE in 28nm. 1-11 - Kevin Deierling:
NVIDIA's Resource Transmutable Network Processing ASIC. 1-14 - Luca Valente, Asif Veeran, Mattia Sinigaglia, Yvan Tortorella, Alessandro Nadalini, Nils Wistoff, Bruno Sá, Angelo Garofalo, Rafail Psiakis, M. Tolba, Ari Kulmala, Nimisha Limaye, Ozgur Sinanoglu, Sandro Pinto, Daniele Palossi, Luca Benini, Baker Mohammad, Davide Rossi:
Shaheen: An Open, Secure, and Scalable RV64 SoC for Autonomous Nano-UAVs. 1-12 - Mark Wade, Chen Sun, Matt Sysak, Vladimir Stojanovic, Pooya Tadayon, Ravi Mahajan, Babak Sabi:
Driving Compute Scale-out Performance with Optical I/O Chiplets in Advanced System-in-Package Platforms. 1 - Sean Lie:
Inside the Cerebras Wafer-Scale Cluster: Cerebras Systems. 1-41 - Mahesh Subramon, David Kramer, Indrani Paul:
AMD Ryzen™ 7040 Series: Technology Overview. 1-27 - Lawrence Spracklen, Subutai Ahmad:
Supercharged AI Inference on Modern CPUs. 1-21 - Zhanhong Tan, Yifu Wu, Yannian Zhang, Haobing Shi, Wuke Zhang, Kaisheng Ma:
A Scalable Multi-Chiplet Deep Learning Accelerator with Hub-Side 2.5D Heterogeneous Integration. 1-17 - Jeff Dean, Amin Vahdat:
Exciting Directions for ML Models and the Implications for Computing Hardware. 1-87 - Srivi Dhruvanarayan, Victor Bittorf:
MLSoC™ - An Overview. 1-13 - Anitha Kona:
CSS N2: Arm Neoverse N2 Platform, Delivered to Partners as a Fully Verified, Customizable Subsystem. 1-23 - Ben Esposito:
Intel Agilex® 9 Direct RF-Series FPGAs with Integrated 64 Gsps Data Converters. 1-35 - Don Soltis, Stephen Robinson:
The Next Generation of High Performance, Energy-Efficient Computing: Intel® Xeon® Processors Built on Efficient-Core. 1-16 - Jin Hyun Kim, Yuhwan Ro, Jinin So, Sukhan Lee, Shinhaeng Kang, YeonGon Cho, Hyeonsu Kim, Byeongho Kim, Kyungsoo Kim, Sangsoo Park, Jin-Seong Kim, Sanghoon Cha, Won-Jo Lee, Jin Jung, Jonggeon Lee, Jieun Lee, Joon-Ho Song, Seungwon Lee, Jeonghyeon Cho, Jaehoon Yu, Kyomin Sohn:
Samsung PIM/PNM for Transfmer Based AI : Energy Efficiency on PIM/PNM Cluster. 1-31 - Maurice Steinman:
Hummingbird™ Low-Latency Computing Engine. 1-20 - Eric Mahurin:
Qualocmm® Hexagon™ NPU. 1-19 - Bill Dally:
Hardware for Deep Learning. 1-58 - Yongkee Kwon, Guhyun Kim, Nahsung Kim, Woojae Shin, Jongsoon Won, Hyunha Joo, Haerang Choi, Byeongju An, Gyeongcheol Shin, Dayeon Yun, Jeongbin Kim, Changhyun Kim, Ilkon Kim, Jaehan Park, Chanwook Park, Yosub Song, Byeongsu Yang, Hyeongdeok Lee, Seungyeong Park, Wonjun Lee, Seongju Lee, Kyuyoung Kim, Daehan Kwon, Chunseok Jeong, John Kim, Euicheol Lim, Junhyun Chun:
Memory-Centric Computing with SK Hynix's Domain-Specific Memory. 1-26 - Magnus Bruce:
Arm Neoverse V2 platform: Leadership Performance and Power Efficiency for Next-Generation Cloud Computing, ML and HPC Workloads. 1-25 - Jason Howard:
The First Direct Mesh-to-Mesh Photonic Fabric. 1-17 - Dharmendra S. Modha, Filipp Akopyan, Alexander Andreopoulos, Rathinakumar Appuswamy, John V. Arthur, Andrew S. Cassidy, Pallab Datta, Michael V. DeBole, Steven K. Esser, Carlos Ortega Otero, Jun Sawada, Brian Taba, Arnon Amir, Deepika Bablani, Peter J. Carlson, Myron D. Flickner, Rajamohan Gandhasri, Guillaume Garreau, Megumi Ito, Jennifer L. Klamo, Jeffrey A. Kusnitz, Nathaniel J. McClatchey, Jeffrey L. McKinstry, Yutaka Y. Nakamura, Tapan K. Nayak, William P. Risk, Kai Schleupen, Ben Shaw, Jay Sivagnaname, Daniel F. Smith, Ignacio Terrizzano, Takanori Ueda:
IBM NorthPole Neural Inference Machine. 1-58 - Dinesh Gaitonde:
AMD Next-Generation FPGA Built from Chiplets. 1-28 - Zhibin Xiao:
Moffett Antoum®: A Deep-Sparse AI Inference System-on-Chip for Vision and Large-language Models. 1-33 - Ian Winfield, Joseph Madril, Tim Ouradnik, Michael Matthews, Guillermo Romero:
FABRIC8LABS: Electrochemical Additive Manufacturing (ECAM) For Cooling High Performance ICs. 1-18 - Kai Troester, Ravi Bhargava:
AMD Next Generation "Zen 4" Core and 4th Gen AMD EPYC™ 9004 Server CPU. 1-25
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