L
Luis Ceze
Researcher at University of Washington
Publications - 256
Citations - 13435
Luis Ceze is an academic researcher from University of Washington. The author has contributed to research in topics: DNA digital data storage & Debugging. The author has an hindex of 48, co-authored 246 publications receiving 11040 citations. Previous affiliations of Luis Ceze include Battelle Memorial Institute & Qualcomm.
Papers
More filters
Proceedings ArticleDOI
TVM: an automated end-to-end optimizing compiler for deep learning
Tianqi Chen,Thierry Moreau,Ziheng Jiang,Lianmin Zheng,Eddie Yan,Meghan Cowan,Haichen Shen,Leyuan Wang,Yuwei Hu,Luis Ceze,Carlos Guestrin,Arvind Krishnamurthy +11 more
TL;DR: TVM as discussed by the authors is a compiler that exposes graph-level and operator-level optimizations to provide performance portability to deep learning workloads across diverse hardware back-ends, such as mobile phones, embedded devices, and accelerators.
Journal ArticleDOI
EnerJ: approximate data types for safe and general low-power computation
TL;DR: EnerJ is developed, an extension to Java that adds approximate data types and a hardware architecture that offers explicit approximate storage and computation and allows a programmer to control explicitly how information flows from approximate data to precise data.
Proceedings ArticleDOI
Neural Acceleration for General-Purpose Approximate Programs
TL;DR: A programming model is defined that allows programmers to identify approximable code regions -- code that can produce imprecise but acceptable results and is faster and more energy efficient than executing the original code.
Proceedings ArticleDOI
An Overview of the BlueGene/L Supercomputer
N. R. Adiga,Gheorghe Almasi,George Almási,Y. Aridor,Rajkishore Barik,D. Beece,Ralph Bellofatto,Gyan Bhanot,R. Bickford,Matthias A. Blumrich,A. A. Bright,Jose R. Brunheroto,Calin Cascaval,José G. Castaños,Waiman Chan,Luis Ceze,Paul W. Coteus,Siddhartha Chatterjee,Dong Chen,G. Chiu,Thomas Mario Cipolla,Paul G. Crumley,K.M. Desai,A. Deutsch,T. Domany,M. B. Dombrowa,Wilm E. Donath,Maria Eleftheriou,C. Christopher Erway,J. Esch,Blake G. Fitch,J. Gagliano,Alan Gara,Rahul Garg,Robert S. Germain,Mark E. Giampapa,B. Gopalsamy,John A. Gunnels,Manish Gupta,Fred G. Gustavson,Shawn A. Hall,R. A. Haring,D. Heidel,P. Heidelberger,L.M. Herger,Dirk Hoenicke,Rory D. Jackson,T. Jamal-Eddine,Gerard V. Kopcsay,Elie Krevat,Manish P. Kurhekar,A.P. Lanzetta,Derek Lieber,L.K. Liu,M. Lu,M. Mendell,A. Misra,Yosef Moatti,L. Mok,José E. Moreira,Ben J. Nathanson,M. Newton,Martin Ohmacht,Adam J. Oliner,Vinayaka Pandit,R.B. Pudota,Rick A. Rand,R. Regan,B. Rubin,Albert E. Ruehli,Silvius Rus,Ramendra K. Sahoo,A. Sanomiya,Eugen Schenfeld,M. Sharma,E. Shmueli,Suryabhan Singh,Peilin Song,Vijayalakshmi Srinivasan,Burkhard Steinmacher-Burow,Karin Strauss,C. Surovic,Richard A. Swetz,Todd E. Takken,R.B. Tremaine,M. Tsao,A. R. Umamaheshwaran,P. Verma,Pavlos M. Vranas,T.J.C. Ward,M. Wazlowski,William A. Barrett,C. Engel,B. Drehmel,B. Hilgart,D. Hill,F. Kasemkhani,D. Krolak,C.T. Li,T. Liebsch,James Anthony Marcella,Adam J. Muff,A. Okomo,M. Rouse,A. Schram,Matthew R. Tubbs,G. Ulsh,Charles D. Wait,J. Wittrup,M. Bae,Kenneth Alan Dockser,Lynn Kissel,M.K. Seager,Jeffrey S. Vetter,K. Yates +114 more
TL;DR: An overview of the BlueGene/L Supercomputer, a massively parallel system of 65,536 nodes based on a new architecture that exploits system-on-a-chip technology to deliver target peak processing power of 360 teraFLOPS (trillion floating-point operations per second).
Journal ArticleDOI
Random access in large-scale DNA data storage
Lee Organick,Siena Dumas Ang,Yuan-Jyue Chen,Randolph Lopez,Sergey Yekhanin,Konstantin Makarychev,Konstantin Makarychev,Miklos Z. Racz,Miklos Z. Racz,Govinda M. Kamath,Govinda M. Kamath,Parikshit Gopalan,Parikshit Gopalan,Bichlien H. Nguyen,Christopher N. Takahashi,Sharon Newman,Sharon Newman,Hsing Yeh Parker,Cyrus Rashtchian,Kendall Stewart,Gagan Gupta,Robert Carlson,John Mulligan,Douglas Carmean,Georg Seelig,Luis Ceze,Karin Strauss +26 more
TL;DR: A large library of primers are designed and validated that enable individual recovery of all files stored within the DNA, and an algorithm is developed that greatly reduces the sequencing read coverage required for error-free decoding by maximizing information from all sequence reads.