Mori Ohara

Publications

• Beyond SPMD: Compiling Triton Kernels for Dataflow AI Architectures

  • • Takuya Nakaike
    • Mori Ohara
  • 2026
  • PyTorch Conference 2026

  Poster

• Automatic Optimize-time Validation for Binary Optimizers

  • • Motohiro Kawahito
    • Reid Copeland
    • et al.
  • 2021
  • Journal of Information Processing

  Paper

• Detecting Layered Bottlenecks in Microservices

  • • Tatsushi Inagaki
    • Yohei Ueda
    • et al.
  • 2022
  • CLOUD 2022

  Conference paper

• RaPiD: AI Accelerator for Ultra-Low Precision Training and Inference

  • • Swagath Venkataramani
    • Vijayalakshmi Srinivasan
    • et al.
  • 2021
  • ISCA 2021

  Conference paper

• Efficient AI System Design with Cross-Layer Approximate Computing

  • • Swagath Venkataramani
    • Xiao Sun
    • et al.
  • 2020
  • Proceedings of the IEEE

  Paper

• Hyperledger Fabric Performance Characterization and Optimization Using GoLevelDB Benchmark

  • • Takuya Nakaike
    • Qi Zhang
    • et al.
  • 2020
  • ICBC 2020

  Conference paper

• DeepTools: Compiler and Execution Runtime Extensions for RaPiD AI Accelerator

  • • Swagath Venkataramani
    • Jungwook Choi
    • et al.
  • 2019
  • IEEE Micro

  Paper

• A Compiler for Deep Neural Network Accelerators to Generate Optimized Code for a Wide Range of Data Parameters from a Hand-crafted Computation Kernel

  • • Eri Ogawa
    • Kazuaki Ishizaki
    • et al.
  • 2019
  • COOL CHIPS 2019

  Conference paper

• Profile-based Detection of Layered Bottlenecks

  • • Tatsushi Inagaki
    • Yohei Ueda
    • et al.
  • 2019
  • ICPE 2019

  Conference paper

• Identifying the potential of near data processing for Apache Spark

  • • Ahsan Javed Awan
    • Eduard Ayguadé
    • et al.
  • 2017
  • MEMSYS 2017

  Conference paper