System Architecture and Software Stack for GDDR6-AiM

Yongkee Kwon,Kornijcuk Vladimir,Nahsung Kim,Woojae Shin,Jongsoon Won,Minkyu Lee,Hyunha Joo,Haerang Choi,Guhyun Kim,Byeongju An,Jeongbin Kim,Jaewook Lee,Ilkon Kim,Jaehan Park,Chanwook Park, Yosub Song, Byeongsu Yang, Hyungdeok Lee,Seho Kim,Daehan Kwon,Seong Ju Lee,Kyuyoung Kim,Sanghoon Oh,Joonhong Park,Gimoon Hong,Dongyoon Ka,Kyudong Hwang,Jeongje Park,Kyeong Pil Kang,Jungyeon Kim,Junyeol Jeon, Myeongjun Lee, Minyoung Shin, Minhwan Shin, Jaekyung Cha, Changson Jung, Kijoon Chang,Chunseok Jeong,Euicheol Lim,Il Park,Junhyun Chun

2022 IEEE Hot Chips 34 Symposium (HCS)（2022）

引用 4|浏览37

关键词

system architecture,GDDR6-based processing-in-memory product sample,accelerator-in-memory,in-memory acceleration,matrix-vector product operations,machine learning applications,all-bank operation support,internal DRAM bandwidth,memory-bound applications,extended command set,software stack design,system-level performance,FMC-based AiM extension cards,software systems,GDDR6-AiM architecture,FPGA-based reference platform

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