Improving GPGPU resource utilization through alternative thread block scheduling by Minseok Lee, Seokwoo Song, Joosik Moon, Kim, John, Woong Seo, Yeongon Cho, Soojung Ryu

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COSMOS: Coordinated Management of Cores, Memory, and Compressed Memory Swap for QoS-Aware and Efficient Workload Consolidation for Memory-Intensive Applications by Han, Myeonggyun, Park, Eunseong, Shin, Youngsam, Oh, Deok-Jae, Cho, Yeongon, Baek, Woongki

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iPAWS: Instruction-issue pattern-based adaptive warp scheduling for GPGPUs by Minseok Lee, Gwangsun Kim, Kim, John, Woong Seo, Yeongon Cho, Soojung Ryu

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Providing cost-effective on-chip network bandwidth in GPGPUs by Hanjoon Kim, Kim, John, Woong Seo, Yeongon Cho, Soojung Ryu

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Near-Memory Processing in Action: Accelerating Personalized Recommendation With AxDIMM by Ke, Liu, Zhang, Xuan, So, Jinin, Lee, Jong-Geon, Kang, Shin-Haeng, Lee, Sukhan, Han, Songyi, Cho, YeonGon, Kim, Jin Hyun, Kwon, Yongsuk, Kim, KyungSoo, Jung, Jin, Yun, Ilkwon, Park, Sung Joo, Park, Hyunsun, Song, Joonho, Cho, Jeonghyeon, Sohn, Kyomin, Kim, Nam Sung, Lee, Hsien-Hsin S.

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Seeded region growing on multi-core system by Sangheon Lee, Yeongon Cho, Soojung Ryu, Byeonghun Lee, Yeong-Gil Shin

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Aquabolt-XL HBM2-PIM, LPDDR5-PIM With In-Memory Processing, and AXDIMM With Acceleration Buffer by Kim, Jin Hyun, Kang, Shin-Haeng, Lee, Sukhan, Kim, Hyeonsu, Ro, Yuhwan, Lee, Seungwon, Wang, David, Choi, Jihyun, So, Jinin, Cho, YeonGon, Song, JoonHo, Cho, Jeonghyeon, Sohn, Kyomin, Kim, Nam Sung

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The Breakthrough Memory Solutions for Improved Performance on LLM Inference by Kim, Byeongho, Cha, Sanghoon, Park, Sangsoo, Lee, Jieun, Lee, Sukhan, Kang, Shin-haeng, So, Jinin, Kim, Kyungsoo, Jung, Jin, Lee, Jong-Geon, Lee, Sunjung, Paik, Yoonah, Kim, Hyeonsu, Kim, Jin-Seong, Lee, Won-Jo, Ro, Yuhwan, Cho, YeonGon, Kim, Jin Hyun, Song, JoonHo, Yu, Jaehoon, Lee, Seungwon, Cho, Jeonghyeon, Sohn, Kyomin

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An LPDDR-based CXL-PNM Platform for TCO-efficient Inference of Transformer-based Large Language Models by Park, Sang-Soo, Kim, KyungSoo, So, Jinin, Jung, Jin, Lee, Jonggeon, Woo, Kyoungwan, Kim, Nayeon, Lee, Younghyun, Kim, Hyungyo, Kwon, Yongsuk, Kim, Jinhyun, Lee, Jieun, Cho, YeonGon, Tai, Yongmin, Cho, Jeonghyeon, Song, Hoyoung, Ahn, Jung Ho, Kim, Nam Sung

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ULP-SRP: Ultra Low-Power Samsung Reconfigurable Processor for Biomedical Applications by Kim, Changmoo, Chung, Mookyoung, Cho, Yeongon, Konijnenburg, Mario, Ryu, Soojung, Kim, Jeongwook

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ULP-SRP: Ultra low power Samsung Reconfigurable Processor for biomedical applications by Changmoo Kim, Mookyoung Chung, Yeongon Cho, Konijnenburg, M., Soojung Ryu, Jeongwook Kim

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Implementation of a volume rendering on coarse-grained reconfigurable multiprocessor by Seunghun Jin, Sangheon Lee, Moo-Kyoung Chung, Yeongon Cho, Soojung Ryu

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Energy-efficient scheduling for memory-intensive GPGPU workloads by Song, Seokwoo, Lee, Minseok, Kim, John, Seo, Woong, Cho, Yeongon, Ryu, Soojung

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Aquabolt-XL: Samsung HBM2-PIM with in-memory processing for ML accelerators and beyond by Kim, Jin Hyun, Kang, Shin-haeng, Lee, Sukhan, Kim, Hyeonsu, Song, Woongjae, Ro, Yuhwan, Lee, Seungwon, Wang, David, Shin, Hyunsung, Phuah, Bengseng, Choi, Jihyun, So, Jinin, Cho, YeonGon, Song, JoonHo, Choi, Jangseok, Cho, Jeonghyeon, Sohn, Kyomin, Sohn, Youngsoo, Park, Kwangil, Kim, Nam Sung

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Samsung PIM/PNM for Transfmer Based AI : Energy Efficiency on PIM/PNM Cluster by Kim, Jin Hyun, Ro, Yuhwan, So, Jinin, Lee, Sukhan, Kang, Shin-haeng, Cho, YeonGon, Kim, Hyeonsu, Kim, Byeongho, Kim, Kyungsoo, Park, Sangsoo, Kim, Jin-Seong, Cha, Sanghoon, Lee, Won-Jo, Jung, Jin, Lee, Jong-Geon, Lee, Jieun, Song, JoonHo, Lee, Seungwon, Cho, Jeonghyeon, Yu, Jaehoon, Sohn, Kyomin

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