Randomizing Packet Memory Networks for Low-Latency Processor-Memory Communication. - Daichi Fujiki; Hiroki Matsutani; Michihiro Koibuchi; Hideharu Amano (PDP, 2016)

In-memory Data Flow Processor. - Daichi Fujiki; Scott A. Mahlke; Reetuparna Das (PACT, 2017)

High-Bandwidth Low-Latency Approximate Interconnection Networks. - Daichi Fujiki; Kiyo Ishii; Ikki Fujiwara; Hiroki Matsutani; Hideharu Amano; Henri Casanova; Michihiro Koibuchi (HPCA, 2017)

In-Memory Data Parallel Processor. - Daichi Fujiki; Scott A. Mahlke; Reetuparna Das (ASPLOS, 2018)

GenAx: A Genome Sequencing Accelerator. - Daichi Fujiki; Arun Subramaniyan 001; Tianjun Zhang; Yu Zeng; Reetuparna Das; David T. Blaauw; Satish Narayanasamy (ISCA, 2018)

AxNoC: Low-power Approximate Network-on-Chips using Critical-Path Isolation. - Akram Ben Ahmed; Daichi Fujiki; Hiroki Matsutani; Michihiro Koibuchi; Hideharu Amano (NOCS, 2018)

Duality cache for data parallel acceleration. - Daichi Fujiki; Scott A. Mahlke; Reetuparna Das (ISCA, 2019)

Near-memory data transformation for efficient sparse matrix multi-vector multiplication. - Daichi Fujiki; Niladrish Chatterjee; Donghyuk Lee; Mike O'Connor (SC, 2019)

A 2.46M reads/s Genome Sequencing Accelerator using a 625 Processing-Element Array. - Zhehong Wang; Tianjun Zhang; Daichi Fujiki; Arun Subramaniyan 001; Xiao Wu 002; Makoto Yasuda; Satoru Miyoshi; Masaru Kawaminami; Reetuparna Das; Satish Narayanasamy; David T. Blaauw (CICC, 2020)

SeedEx: A Genome Sequencing Accelerator for Optimal Alignments in Subminimal Space. - Daichi Fujiki; Shunhao Wu; Nathan Ozog; Kush Goliya; David T. Blaauw; Satish Narayanasamy; Reetuparna Das (MICRO, 2020)

A 2.46M Reads/s Seed-Extension Accelerator for Next-Generation Sequencing Using a String-Independent PE Array. - Zhehong Wang; Tianjun Zhang; Daichi Fujiki; Arun Subramaniyan 001; Xiao Wu 002; Makoto Yasuda; Satoru Miyoshi; Masaru Kawaminami; Reetuparna Das; Satish Narayanasamy; David T. Blaauw (IEEE J. Solid State Circuits, 2021)

In-/Near-Memory Computing - Daichi Fujiki; Xiaowei Wang; Arun Subramaniyan 001; Reetuparna Das (Morgan & Claypool Publishers, 2021)

Multi-Layer In-Memory Processing. - Daichi Fujiki; Alireza Khadem; Scott A. Mahlke; Reetuparna Das (MICRO, 2022)

In-Memory Acceleration for General Data Parallel Applications - Daichi Fujiki (2022)

Vector-Processing for Mobile Devices: Benchmark and Analysis. - Alireza Khadem; Daichi Fujiki; Nishil Talati; Scott A. Mahlke; Reetuparna Das (IISWC, 2023)

MVC: Enabling Fully Coherent Multi-Data-Views through the Memory Hierarchy with Processing in Memory. - Daichi Fujiki (MICRO, 2023)

HALO-CAT: A Hidden Network Processor with Activation-Localized CIM Architecture and Layer-Penetrative Tiling. - Yung-Chin Chen; Shimpei Ando; Daichi Fujiki; Shinya Takamaeda-Yamazaki; Kentaro Yoshioka (CoRR, 2023)

OSA-HCIM: On-The-Fly Saliency-Aware Hybrid SRAM CIM with Dynamic Precision Configuration. - Yung-Chin Chen; Shimpei Ando; Daichi Fujiki; Shinya Takamaeda-Yamazaki; Kentaro Yoshioka (ASPDAC, 2024)

WhiteDwarf: 12.24 TFLOPS/W 40 nm Versatile Neural Inference Engine for Ultra-Compact Execution of CNNs and MLPs Through Triple Unstructured Sparsity Exploitation and Triple Model Compression. - Yasuyuki Okoshi; Ángel López García-Arias; Jaehoon Yu; Junnosuke Suzuki; Hikari Otsuka; Thiem Van Chu; Kazushi Kawamura; Daichi Fujiki; Masato Motomura (A-SSCC, 2024)

Exploiting N:M Sparsity in Quantized-Folded ResNets: Signed Multicoat Supermasks and Iterative Pruning-Quantization. - Akihiro Shioda; Ángel López García-Arias; Hikari Otsuka; Yuki Ichikawa; Yasuyuki Okoshi; Kazushi Kawamura; Thiem Van Chu; Daichi Fujiki; Masato Motomura (CANDAR, 2024)

The Case for Coherence Directories in Memory Cubes. - Yuki Kameyama; Naoya Niwa; Daichi Fujiki; Hiroki Matsutani; Michihiro Koibuchi; Hideharu Amano (MCSoC, 2024)

Partial Search in a Frozen Network is Enough to Find a Strong Lottery Ticket. - Hikari Otsuka; Daiki Chijiwa; Ángel López García-Arias; Yasuyuki Okoshi; Kazushi Kawamura; Thiem Van Chu; Daichi Fujiki; Susumu Takeuchi; Masato Motomura (CoRR, 2024)

Restricted Random Pruning at Initialization for High Compression Range. - Hikari Otsuka; Yasuyuki Okoshi; Ángel López García-Arias; Kazushi Kawamura; Thiem Van Chu; Daichi Fujiki; Masato Motomura (Trans. Mach. Learn. Res., 2024)

TTF-GNN: Memory-Efficient GNNs via Tensor Train Decomposition and Network Folding. - Hiroaki Ito; Jiale Yan; Kazushi Kawamura; Masato Motomura; Thiem Van Chu; Daichi Fujiki (COOL CHIPS, 2025)

Multi-Dimensional Vector ISA Extension for Mobile In-Cache Computing. - Alireza Khadem; Daichi Fujiki; Hilbert Chen; Yufeng Gu; Nishil Talati; Scott A. Mahlke; Reetuparna Das (HPCA, 2025)

DX100: Programmable Data Access Accelerator for Indirection. - Alireza Khadem; Kamalavasan Kamalakkannan; Zhenyan Zhu; Akash Poptani; Yufeng Gu; Jered Benjamin Dominguez-Trujillo; Nishil Talati; Daichi Fujiki; Scott A. Mahlke; Galen M. Shipman; Reetuparna Das (ISCA, 2025)

BingoGCN: Towards Scalable and Efficient GNN Acceleration with Fine-Grained Partitioning and SLT. - Jiale Yan; Hiroaki Ito; Yuta Nagahara; Kazushi Kawamura; Masato Motomura; Thiem Van Chu; Daichi Fujiki (ISCA, 2025)

WhiteDwarf: A Holistic Co-Design Approach to Ultra-Compact Neural Inference Acceleration. - Ángel López García-Arias; Yasuyuki Okoshi; Jaehoon Yu; Junnosuke Suzuki; Hikari Otsuka; Kazushi Kawamura; Thiem Van Chu; Daichi Fujiki; Masato Motomura (IEEE Access, 2025)

Uncovering Strong Lottery Tickets in Graph Transformers: A Path to Memory Efficient and Robust Graph Learning. - Hiroaki Ito; Jiale Yan; Hikari Otsuka; Kazushi Kawamura; Masato Motomura; Thiem Van Chu; Daichi Fujiki (Trans. Mach. Learn. Res., 2025)

Partially Frozen Random Networks Contain Compact Strong Lottery Tickets. - Hikari Otsuka; Daiki Chijiwa; Ángel López García-Arias; Yasuyuki Okoshi; Kazushi Kawamura; Thiem Van Chu; Daichi Fujiki; Susumu Takeuchi; Masato Motomura (Trans. Mach. Learn. Res., 2025)

DMSA: An Efficient Architecture for Sparse-Sparse Matrix Multiplication Based on Distribute-Merge Product Dataflow. - Yuta Nagahara; Jiale Yan; Kazushi Kawamura; Daichi Fujiki; Masato Motomura; Thiem Van Chu (IEEE Trans. Very Large Scale Integr. Syst., 2025)

AdaBlock-dLLM: Semantic-Aware Diffusion LLM Inference via Adaptive Block Size. - Guanxi Lu; Hao Mark Chen; Yuto Karashima; Zhican Wang; Daichi Fujiki; Hongxiang Fan (CoRR, 2025)