3 citations · 6 across the 15 of their papers we have counts for
7 papers · 1 filter
PUDTune: Multi-Level Charging for High-Precision Calibration in Processing-Using-DRAM
Tatsuya Kubo, Daichi Tokuda, Lei Qu +2
Recently, practical analog in-memory computing has been realized using unmodified commercial DRAM modules. The underlying Processing-Using-DRAM (PUD) techniques enable high-through…
TRIP-Shapley: Propagation-Aware Contribution Attribution Framework for Peer-to-Peer Federated Learning
Honoka Anada, Tatsuya Kaneko, Yafei Ou +1
Contribution attribution is a fundamental problem in federated learning (FL), yet it remains challenging in peer-to-peer FL (P2PFL), where participant influence propagates through…
PRIOT: Pruning-Based Integer-Only Transfer Learning for Embedded Systems
Honoka Anada, Sefutsu Ryu, Masayuki Usui +2
On-device transfer learning is crucial for adapting a common backbone model to the unique environment of each edge device. Tiny microcontrollers, such as the Raspberry Pi Pico, are…
MVDRAM: Enabling GeMV Execution in Unmodified DRAM for Low-Bit LLM Acceleration
Tatsuya Kubo, Daichi Tokuda, Tomoya Nagatani +4
General matrix-vector multiplication (GeMV) remains a critical latency bottleneck in large language model (LLM) inference, even with quantized low-bit models. Processing-Using-DRAM…
RustSFQ: A Domain-Specific Language for SFQ Circuit Design
Mebuki Oishi, Sun Tanaka, Shinya Takamaeda-Yamazaki
Cell-based design of a single-flux-quantum (SFQ) digital circuit requires input-output consistency; every output signal must be consumed only once by the input of the following com…
Exploring the Versal AI Engine for 3D Gaussian Splatting
Kotaro Shimamura, Ayumi Ohno, Shinya Takamaeda-Yamazaki
Dataflow-oriented spatial architectures are the emerging paradigm for higher computation performance and efficiency. AMD Versal AI Engine is a commercial spatial architecture consi…
Accelerating Elliptic Curve Point Additions on Versal AI Engine for Multi-scalar Multiplication
Ayumi Ohno, Kotaro Shimamura, Shinya Takamaeda-Yamazaki
Multi-scalar multiplication (MSM) is crucial in cryptographic applications and computationally intensive in zero-knowledge proofs. MSM involves accumulating the products of scalars…