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34th Hot Chips Symposium 2022: Cupertino, CA, USA
- 2022 IEEE Hot Chips 34 Symposium, HCS 2022, Cupertino, CA, USA, August 21-23, 2022. IEEE 2022, ISBN 978-1-6654-6028-6
- Alan Smith, Norman James:
AMD Instinct™ MI200 Series Accelerator and Node Architectures. 1-23 - Sean Lie:
Cerebras Architecture Deep Dive: First Look Inside the HW/SW Co-Design for Deep Learning : Cerebras Systems. 1-34 - Alexander Ishii, Ryan Wells:
The Nvlink-Network Switch: Nvidia's Switch Chip for High Communication-Bandwidth Superpods. 1-23 - Mediatek Ericbill Wang, Arm Stefan Rosinger, Saurabh Pradhan:
Dimensity 9000 - A Flagship Smartphone SoC. 1-23 - Sangyeob Kim, Sangjin Kim, Soyeon Um, Soyeon Kim, Kwantae Kim, Hoi-Jun Yoo:
Neuro-CIM: A 310.4 TOPS/W Neuromorphic Computing-in-Memory Processor with Low WL/BL activity and Digital-Analog Mixed-mode Neuron Firing. 1-25 - Wilfred Gomes, Slade Morgan, Boyd Phelps, Tim Wilson, Erik Hallnor:
Meteor Lake and Arrow Lake Intel Next-Gen 3D Client Architecture Platform with Foveros. 1-40 - Emil Talpes, Douglas Williams, Debjit Das Sarma:
DOJO: The Microarchitecture of Tesla's Exa-Scale Computer. 1-28 - Jaideep Dastidar, David Riddoch, Jason Moore, Steve Pope, Jim Wesselkamper:
AMD 400G Adaptive SmartNIC SoC: Technology preview. 1-31 - Richard Grisenthwaite:
Arm Morello Evaluation Platform -Validating CHERI-based Security in a High-performance System. 1-22 - Jack Choquette:
Nvidia Hopper GPU: Scaling Performance. 1-46 - Serena Curzel
, Nicolas Bohm Agostini, Reece Neff, Ankur Limaye
From High-Level Frameworks to custom Silicon with SODA. 1-13 - Jonathon Evans:
Nvidia Grace. 1-20 - Yao-Chung Hsu, Atsutake Kosuge, Rei Sumikawa, Kota Shiba
A 13.7μJ/prediction 88% Accuracy CIFAR-10 Single-Chip Wired-logic Processor in 16-nm FPGA using Non-Linear Neural Network. 1-14 - Ji-Hoon Kim, Seunghee Han, Kwanghyun Park
Trinity: End-to-End In-Database Near-Data Machine Learning Acceleration Platform for Advanced Data Analytics. 1-16 - Ameer Abdelhadi, Eugene Sha, Andreas Moshovos:
A Massive-Scale Brain Activity Decoding Chip. 1-65 - Mike Hong, Lingjie Xu:
壁仞™ BR100 GPGPU: Accelerating Datacenter Scale AI Computing. 1-22 - Dongseok Im, Gwangtae Park, Zhiyong Li
DSPU: A 281.6mW Real-Time Deep Learning-Based Dense RGB-D Data Acquisition with Sensor Fusion and 3D Perception System-on-Chip. 1-25 - Blaise Tine, Varun Saxena, Santosh Srivatsan, Joshua R. Simpson, Fadi Alzammar, Liam Paul Cooper, Sam Jijina
Accelerating Graphic Rendering on Programmable RISC-V GPUs. 1-15 - Michael Ditty:
NVIDIA ORIN System-On-Chip. 1-17 - Zhiyong Li
An Efficient High-quality FHD Super-resolution Mobile Accelerator SoC with Hybrid-precision and Energy-efficient Cache. 1-26 - Abhishek Bhattacharjee, Rajit Manohar:
HALO: A Flexible and Low Power Processing Fabric for Brain-Computer Interfaces. 1-37 - Praveen Mosur:
Built for the Edge: The Next-Generation Intel® Xeon D 2700 & 1700 processors. 1-15 - Pat Gelsinger:
Semiconductors Run the World : Hot Chips 2022. 1-19 - Sergey Y. Shumarayev, Allen Chan, Tim Hoang, Robert Keller:
Heterogenous Integration Enables FPGA Based Hardware Acceleration for RF Applications. 1-20 - Kathleen Feng, Alex Carsello, Taeyoung Kong, Kalhan Koul, Qiaoyi Liu, Jackson Melchert, Gedeon Nyengele, Maxwell Strange, Keyi Zhang, Ankita Nayak, Jeff Setter, James Thomas, Kavya Sreedhar, Po-Han Chen, Nikhil Bhagdikar, Zachary Myers, Brandon D'Agostino, Pranil Joshi, Stephen Richardson, Rick Bahr, Christopher Torng, Mark Horowitz, Priyanka Raina:
Amber: Coarse-Grained Reconfigurable Array-Based SoC for Dense Linear Algebra Acceleration. 1-30 - Kenji Tanaka, Yuki Arikawa, Kazutaka Morita, Tsuyoshi Ito, Takashi Uchida, Natsuko Saito, Shinya Kaji, Takeshi Sakamoto:
VTA-NIC: Deep Learning Inference Serving in Network Interface Cards. 1-16 - Robert Beachler, Martin Snelgrove:
Untether Ai : Boqueria. 1-19 - Hyunsung Kim, Sungyeob Yoo, Jaewan Bae, Kyeongryeol Bong, Yoonho Boo, Karim Charfi, Hyo-Eun Kim, Hyun Suk Kim, Jinseok Kim, Byungjae Lee, Jaehwan Lee, Myeongbo Shim, Sungho Shin, Jeong Seok Woo, Joo-Young Kim, Sunghyun Park, Jinwook Oh:
LightTrader : World's first AI-enabled High-Frequency Trading Solution with 16 TFLOPS / 64 TOPS Deep Learning Inference Accelerators. 1-10 - Christoph Schulien:
Enabling Scalable Application-Specific Optical Engines (ASOE) by Monolithic Integration of Photonics and Electronics. 1-32 - Alfio Di Mauro, Moritz Scherer, Davide Rossi, Luca Benini:
Kraken: A Direct Event/Frame-Based Multi-sensor Fusion SoC for Ultra-Efficient Visual Processing in Nano-UAVs. 1-19 - Kota Shiba
A 7-nm FinFET 1.2-TB/s/mm2 3D-Stacked SRAM with an Inductive Coupling Interface Using Over-SRAM Coils and Manchester-Encoded Synchronous Transceivers. 1-14 - Miryeong Kwon, Donghyun Gouk, Sangwon Lee
Large-scale Graph Neural Network Services through Computational SSD and In-Storage Processing Architectures. 1-25 - Donghyeon Han, Dongseok Im, Gwangtae Park, Youngwoo Kim, Seokchan Song, Juhyoung Lee, Hoi-Jun Yoo:
HNPU-V2: A 46.6 FPS DNN Training Processor for Real-World Environmental Adaptation based Robust Object Detection on Mobile Devices. 1-18 - Bill Chang, Rajiv Kurian, Doug Williams, Eric Quinnell:
DOJO: Super-Compute System Scaling for ML Training. 1-45 - Seongmin Hong, Seungjae Moon, Junsoo Kim, Sungjae Lee, Minsub Kim
DFX: A Low-latency Multi-FPGA Appliance for Accelerating Transformer-based Text Generation. 1-17 - Wenqi Ji, Yuxing Han, Jiangtao Wen, Yubin Hu
Vision Perception Unit: Next-Generation Smart CMOS Image Sensor. 1-13 - Yongkee Kwon, Kornijcuk Vladimir, Nahsung Kim, Woojae Shin, Jongsoon Won, Minkyu Lee, Hyunha Joo, Haerang Choi, Guhyun Kim, Byeongju An, Jeongbin Kim
System Architecture and Software Stack for GDDR6-AiM. 1-25 - Dennis Abts, John Kim, Garrin Kimmell, Matthew Boyd, Kris Kang, Sahil Parmar, Andrew C. Ling, Andrew Bitar, Ibrahim Ahmed, Jonathan Ross:
The Groq Software-defined Scale-out Tensor Streaming Multiprocessor : From chips-to-systems architectural overview. 1-69 - Hong Jiang:
Intel's Ponte Vecchio GPU : Architecture, Systems & Software. 1-29 - Jim Gibney:
AMD Ryzen™ 6000 Series for Mobile : Technology Overview. 1-24 - Sung Joo Park, H. Kim, K.-S. Kim, J. So, J. Ahn, W.-J. Lee, D. Kim, Young-Ju Kim, J. Seok, J.-G. Lee, H.-Y. Ryu, C. Y. Lee, J. Prout, K.-C. Ryoo, S.-J. Han, M.-K. Kook, J. S. Choi, J. Gim, Y. S. Ki, S. Ryu, C. Park, D.-G. Lee, J. Cho, H. Song, Jin-Yup Lee:
Scaling of Memory Performance and Capacity with CXL Memory Expander. 1-27
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