K
Kazuaki Ishizaki
Researcher at IBM
Publications - 13
Citations - 105
Kazuaki Ishizaki is an academic researcher from IBM. The author has contributed to research in topics: Code (cryptography) & Compiler. The author has an hindex of 2, co-authored 13 publications receiving 27 citations.
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Proceedings ArticleDOI
RaPiD: AI accelerator for ultra-low precision training and inference
Swagath Venkataramani,Vijayalakshmi Srinivasan,Wei Wang,Sanchari Sen,Jintao Zhang,Ankur Agrawal,Monodeep Kar,Shubham Jain,Alberto Mannari,Hoang Tran,Li Yulong,Eri Ogawa,Kazuaki Ishizaki,Hiroshi Inoue,Marcel Schaal,Mauricio J. Serrano,Jungwook Choi,Xiao Sun,Naigang Wang,Chia-Yu Chen,Allison Allain,James Bonano,Nianzheng Cao,Robert Casatuta,Matthew Cohen,Bruce M. Fleischer,Michael A. Guillorn,Howard M. Haynie,Jinwook Jung,Mingu Kang,Kyu-hyoun Kim,Siyu Koswatta,Sae Kyu Lee,Martin Lutz,Silvia Melitta Mueller,Jinwook Oh,Ashish Ranjan,Zhibin Ren,Scot H. Rider,Kerstin Schelm,Michael R. Scheuermann,Joel Abraham Silberman,Jie Yang,Vidhi Zalani,Xin Zhang,Ching Zhou,Matt Ziegler,Vinay Velji Shah,Moriyoshi Ohara,Pong-Fei Lu,Brian W. Curran,Sunil Shukla,Leland Chang,Kailash Gopalakrishnan +53 more
TL;DR: RaPiD1 as mentioned in this paper is a 4-core AI accelerator chip supporting a spectrum of precisions, namely, 16 and 8-bit floating-point and 4 and 2-bit fixed-point.
Journal ArticleDOI
Efficient AI System Design With Cross-Layer Approximate Computing
Swagath Venkataramani,Xiao Sun,Naigang Wang,Chia-Yu Chen,Jungwook Choi,Mingu Kang,Ankur Agarwal,Jinwook Oh,Shubham Jain,Tina Babinsky,Nianzheng Cao,Thomas W. Fox,Bruce M. Fleischer,George D. Gristede,Michael A. Guillorn,Howard M. Haynie,Hiroshi Inoue,Kazuaki Ishizaki,Michael J. Klaiber,Shih-Hsien Lo,Gary W. Maier,Silvia Melitta Mueller,Michael R. Scheuermann,Eri Ogawa,Marcel Schaal,Mauricio J. Serrano,Joel Abraham Silberman,Christos Vezyrtzis,Wei Wang,Fanchieh Yee,Jintao Zhang,Matthew M. Ziegler,Ching Zhou,Moriyoshi Ohara,Pong-Fei Lu,Brian W. Curran,Sunil Shukla,Vijayalakshmi Srinivasan,Leland Chang,Kailash Gopalakrishnan +39 more
TL;DR: RaPiD, a multi-tera operations per second (TOPS) AI hardware accelerator core that is built from the ground-up using AxC techniques across the stack including algorithms, architecture, programmability, and hardware, is presented.
Journal ArticleDOI
DeepTools : Compiler and Execution Runtime Extensions for RaPiD AI Accelerator
Swagath Venkataramani,Jungwook Choi,Vijayalakshmi Srinivasan,Wei Wang,Jintao Zhang,Marcel Schaal,Mauricio J. Serrano,Kazuaki Ishizaki,Hiroshi Inoue,Eri Ogawa,Moriyoshi Ohara,Leland Chang,Kailash Gopalakrishnan +12 more
TL;DR: A significant first step towards this goal is taken and an end-to-end software stack for the RaPiD AI accelerator developed by IBM Research is presented and a set of software extensions, called Deeptools, that leverage and work within popular deep learning frameworks are presented.
Proceedings ArticleDOI
Analyzing and Optimizing Java Code Generation for Apache Spark Query Plan
TL;DR: Two types of problems were analyzed by inspecting generated code, namely, access to column-oriented storage and to a primitive-type array, and optimizations that can eliminate inefficient code were devised to solve the issues.
Proceedings ArticleDOI
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,Hiroshi Inoue,Swagath Venkataramani,Jungwook Choi,Wei Wang,Vijayalakshmi Srinivasan,Moriyoshi Ohara,Kailash Gopalakrishnan +8 more
TL;DR: This paper presents the design and implementation of a compiler for a deep neural network accelerator that provides high performance and energy efficiency, and can generate code for five most-critical deep learning operators with a comparative performance obtained from hand- tuned code.