Mark Horowitz

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John L. Hennessy (22)
Christos Kozyrakis (16)
Marc S Levoy (15)
Anoop Gupta (14)
Michael D Smith (11)
Richard Thomas Simoni (11)
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Mark Andrew Heinrich (10)
Ofer Shacham (10)
Stephen E Richardson (10)
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Andrew Adams (9)
Eino Ville Talvala (8)
Mendel Rosenblum (8)
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Jeffrey Scott Kuskin (6)
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ACM SIGARCH Computer Architecture News (24)
ACM Transactions on Graphics (8)
ACM SIGPLAN Notices (6)
ACM SIGOPS Operating Systems Review (5)
Communications of the ACM (4)
ACM Transactions on Computer Systems (3)
IEEE Micro (3)
ACM Transactions on Architecture and Code Optimization (2)
Queue (2)
Computer (1)
IEEE Design & Test (1)
IEEE Transactions on Computers (1)
Integration, the VLSI Journal (1)
Journal of VLSI Signal Processing Systems (1)
Operations Research (1)
Parallel Computing (1)

Proceedings/Book Names

DATE '10: Proceedings of the Conference on Design, Automation and Test in Europe (3)
ASPLOS 2023: Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 3 (2)
ASPLOS IX: Proceedings of the ninth international conference on Architectural support for programming languages and operating systems (2)
ASPLOS VI: Proceedings of the sixth international conference on Architectural support for programming languages and operating systems (2)
DAC '03: Proceedings of the 40th annual Design Automation Conference (2)
DAC '07: Proceedings of the 44th annual Design Automation Conference (2)
DAC '10: Proceedings of the 47th Design Automation Conference (2)
DAC '11: Proceedings of the 48th Design Automation Conference (2)
DAC '12: Proceedings of the 49th Annual Design Automation Conference (2)
DAC '87: Proceedings of the 24th ACM/IEEE Design Automation Conference (2)
DAC '99: Proceedings of the 36th annual ACM/IEEE Design Automation Conference (2)
ICCAD '99: Proceedings of the 1999 IEEE/ACM international conference on Computer-aided design (2)
ISCA '88: Proceedings of the 15th Annual International Symposium on Computer architecture (2)
ISCA '98: 25 years of the international symposia on Computer architecture (selected papers) (2)
MICRO 42: Proceedings of the 42nd Annual IEEE/ACM International Symposium on Microarchitecture (2)
SIGGRAPH '05: ACM SIGGRAPH 2005 Papers (2)
ISCA '91: Proceedings of the 18th annual international symposium on Computer architecture (1)
SIGGRAPH '04: ACM SIGGRAPH 2004 Papers (1)
SIGGRAPH '06: ACM SIGGRAPH 2006 Papers (1)
SIGGRAPH '07: ACM SIGGRAPH 2007 papers (1)

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Proceedings (99)
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Other periodicals (11)
Magazines (6)
Reports (6)
Books (3)

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Research Article (59)
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Association for Computing Machinery (117)
IEEE Computer Society (17)
IEEE Computer Society Press (12)
IEEE Press (10)
Stanford University (6)
European Design and Automation Association (3)
Elsevier Science Publishers B. V. (2)
Kluwer Academic Publishers (2)
MIT Press (2)
EDA Consortium (1)
INFORMS (1)
Junction Publishing (1)
Morgan Kaufmann Publishers Inc. (1)
Springer-Verlag (1)

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Improving Energy Efficiency of CGRAs with Low-Overhead Fine-Grained Power Domains
- Ankita Nayak
  Stanford University, Stanford, CA
  ,
- Keyi Zhang
  Stanford University, Stanford, CA
  ,
- Rajsekhar Setaluri
  Stanford University, Stanford, CA
  ,
- Alex Carsello
  Stanford University, Stanford, CA
  ,
- Makai Mann
  Stanford University, Stanford, CA
  ,
- Christopher Torng
  Stanford University, Stanford, CA
  ,
- Stephen Richardson
  Stanford University, Stanford, CA
  ,
- Rick Bahr
  Stanford University, Stanford, CA
  ,
- Pat Hanrahan
  Stanford University, Stanford, CA
  ,
- Mark Horowitz
  Stanford University, Stanford, CA
  ,
- Priyanka Raina
  Stanford University, Stanford, CA
ACM Transactions on Reconfigurable Technology and Systems, Volume 16, Issue 2•June 2023, Article No.: 26, pp 1-28 • https://doi.org/10.1145/3558394
To effectively minimize static power for a wide range of applications, power domains for coarse-grained reconfigurable array (CGRA) architectures need to be more fine-grained than those found in a typical application-specific integrated circuit. However, ...
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APEX: A Framework for Automated Processing Element Design Space Exploration using Frequent Subgraph Analysis
- Jackson Melchert
  Stanford University, USA
  ,
- Kathleen Feng
  Stanford University, USA
  ,
- Caleb Donovick
  Stanford University, USA
  ,
- Ross Daly
  Stanford University, USA
  ,
- Ritvik Sharma
  Stanford University, USA
  ,
- Clark Barrett
  Stanford University, USA
  ,
- Mark A. Horowitz
  Stanford University, USA
  ,
- Pat Hanrahan
  Stanford University, USA
  ,
- Priyanka Raina
  Stanford University, USA
ASPLOS 2023: Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 3•March 2023, pp 33-45• https://doi.org/10.1145/3582016.3582070

The architecture of a coarse-grained reconfigurable array (CGRA) processing element (PE) has a significant effect on the performance and energy-efficiency of an application running on the CGRA. This paper presents APEX, an automated approach for ...
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The Sparse Abstract Machine
- Olivia Hsu
  Stanford University, USA
  ,
- Maxwell Strange
  Stanford University, USA
  ,
- Ritvik Sharma
  Stanford University, USA
  ,
- Jaeyeon Won
  Massachusetts Institute of Technology, USA
  ,
- Kunle Olukotun
  Stanford University, USA
  ,
- Joel S. Emer
  Massachusetts Institute of Technology, USA / NVIDIA, USA
  ,
- Mark A. Horowitz
  Stanford University, USA
  ,
- Fredrik Kjølstad
  Stanford University, USA
ASPLOS 2023: Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 3•March 2023, pp 710-726• https://doi.org/10.1145/3582016.3582051

We propose the Sparse Abstract Machine (SAM), an abstract machine model for targeting sparse tensor algebra to reconfigurable and fixed-function spatial dataflow accelerators. SAM defines a streaming dataflow abstraction with sparse primitives that ...
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Unified Buffer: Compiling Image Processing and Machine Learning Applications to Push-Memory Accelerators
- Qiaoyi Liu
  Stanford University, Stanford, CA, USA
  ,
- Jeff Setter
  Stanford University, Stanford, CA, USA
  ,
- Dillon Huff
  Stanford University, Stanford, CA, USA
  ,
- Maxwell Strange
  Stanford University, Stanford, CA, USA
  ,
- Kathleen Feng
  Stanford University, Stanford, CA, USA
  ,
- Mark Horowitz
  Stanford University, Stanford, CA, USA
  ,
- Priyanka Raina
  Stanford University, Stanford, CA, USA
  ,
- Fredrik Kjolstad
  Stanford University, Stanford, CA, USA
ACM Transactions on Architecture and Code Optimization, Volume 20, Issue 2•June 2023, Article No.: 26, pp 1-26 • https://doi.org/10.1145/3572908
Image processing and machine learning applications benefit tremendously from hardware acceleration. Existing compilers target either FPGAs, which sacrifice power and performance for programmability, or ASICs, which become obsolete as applications change. ...
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AHA: An Agile Approach to the Design of Coarse-Grained Reconfigurable Accelerators and Compilers
- Kalhan Koul
  Stanford University, Stanford, California, USA
  ,
- Jackson Melchert
  Stanford University, Stanford, California, USA
  ,
- Kavya Sreedhar
  Stanford University, Stanford, California, USA
  ,
- Leonard Truong
  Stanford University, Stanford, California, USA
  ,
- Gedeon Nyengele
  Stanford University, Stanford, California, USA
  ,
- Keyi Zhang
  Stanford University, Stanford, California, USA
  ,
- Qiaoyi Liu
  Stanford University, Stanford, California, USA
  ,
- Jeff Setter
  Stanford University, Stanford, California, USA
  ,
- Po-Han Chen
  Stanford University, Stanford, California, USA
  ,
- Yuchen Mei
  Stanford University, Stanford, California, USA
  ,
- Maxwell Strange
  Stanford University, Stanford, California, USA
  ,
- Ross Daly
  Stanford University, Stanford, California, USA
  ,
- Caleb Donovick
  Stanford University, Stanford, California, USA
  ,
- Alex Carsello
  Stanford University, Stanford, California, USA
  ,
- Taeyoung Kong
  Stanford University, Stanford, California, USA
  ,
- Kathleen Feng
  Stanford University, Stanford, California, USA
  ,
- Dillon Huff
  Stanford University, Stanford, California, USA
  ,
- Ankita Nayak
  Stanford University, Stanford, California, USA
  ,
- Rajsekhar Setaluri
  Stanford University, Stanford, California, USA
  ,
- James Thomas
  Stanford University, Stanford, California, USA
  ,
- Nikhil Bhagdikar
  Stanford University, Stanford, California, USA
  ,
- David Durst
  Stanford University, Stanford, California, USA
  ,
- Zachary Myers
  Stanford University, Stanford, California, USA
  ,
- Nestan Tsiskaridze
  Stanford University, Stanford, California, USA
  ,
- Stephen Richardson
  Stanford University, Stanford, California, USA
  ,
- Rick Bahr
  Stanford University, Stanford, California, USA
  ,
- Kayvon Fatahalian
  Stanford University, Stanford, California, USA
  ,
- Pat Hanrahan
  Stanford University, Stanford, California, USA
  ,
- Clark Barrett
  Stanford University, Stanford, California, USA
  ,
- Mark Horowitz
  Stanford University, Stanford, California, USA
  ,
- Christopher Torng
  Stanford University, Stanford, California, USA
  ,
- Fredrik Kjolstad
  Stanford University, Stanford, California, USA
  ,
- Priyanka Raina
  Stanford University, Stanford, California, USA
ACM Transactions on Embedded Computing Systems, Volume 22, Issue 2•March 2023, Article No.: 35, pp 1-34 • https://doi.org/10.1145/3534933
With the slowing of Moore’s law, computer architects have turned to domain-specific hardware specialization to continue improving the performance and efficiency of computing systems. However, specialization typically entails significant modifications to ...
2Citation
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Bringing source-level debugging frameworks to hardware generators
- Keyi Zhang
  Stanford University
  ,
- Zain Asgar
  Stanford University
  ,
- Mark Horowitz
  Stanford University
DAC '22: Proceedings of the 59th ACM/IEEE Design Automation Conference•July 2022, pp 1171-1176• https://doi.org/10.1145/3489517.3530603

High-level hardware generators have significantly increased the productivity of design engineers. They use software engineering constructs to reduce the repetition required to express complex designs and enable more composability. However, these ...
1Citation
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SegAlign: a scalable GPU-based whole genome aligner
- Sneha D. Goenka
  Stanford University
  ,
- Yatish Turakhia
  University of California
  ,
- Benedict Paten
  University of California
  ,
- Mark Horowitz
  Stanford University
SC '20: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis•November 2020, Article No.: 39, pp 1-13

Pairwise Whole Genome Alignment (WGA) is a crucial first step to understanding evolution at the DNA sequence-level. Pairwise WGA of thousands of currently available species genomes could help make biological discoveries, however, computing them for even ...
1Citation
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Interstellar: Using Halide's Scheduling Language to Analyze DNN Accelerators
- Xuan Yang
  Stanford University, Stanford, CA, USA
  ,
- Mingyu Gao
  Tsinghua University, Beijing, China
  ,
- Qiaoyi Liu
  Stanford University, Stanford, CA, USA
  ,
- Jeff Setter
  Stanford University, Stanford, CA, USA
  ,
- Jing Pu
  Stanford University, Stanford, CA, USA
  ,
- Ankita Nayak
  Stanford University, Stanford, CA, China
  ,
- Steven Bell
  Stanford University, Stanford, CA, USA
  ,
- Kaidi Cao
  Stanford University, Stanford, CA, USA
  ,
- Heonjae Ha
  Stanford University, Stanford, CA, USA
  ,
- Priyanka Raina
  Stanford University, Stanford, CA, USA
  ,
- Christos Kozyrakis
  Stanford University, Google, Stanford, CA, USA
  ,
- Mark Horowitz
  Stanford University, Stanford, CA, USA
ASPLOS '20: Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems•March 2020, pp 369-383• https://doi.org/10.1145/3373376.3378514

We show that DNN accelerator micro-architectures and their program mappings represent specific choices of loop order and hardware parallelism for computing the seven nested loops of DNNs, which enables us to create a formal taxonomy of all existing ...
89Citation
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TANGRAM: Optimized Coarse-Grained Dataflow for Scalable NN Accelerators
- Mingyu Gao
  Stanford University & Tsinghua University, Stanford, CA, USA
  ,
- Xuan Yang
  Stanford University, Stanford, CA, USA
  ,
- Jing Pu
  Stanford University & Google, Inc., Stanford, CA, USA
  ,
- Mark Horowitz
  Stanford University, Stanford, CA, USA
  ,
- Christos Kozyrakis
  Stanford University & Google, Inc., Stanford, CA, USA
ASPLOS '19: Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems•April 2019, pp 807-820• https://doi.org/10.1145/3297858.3304014

The use of increasingly larger and more complex neural networks (NNs) makes it critical to scale the capabilities and efficiency of NN accelerators. Tiled architectures provide an intuitive scaling solution that supports both coarse-grained parallelism ...
61Citation
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Fast FPGA Emulation of Analog Dynamics in Digitally-Driven Systems
- Steven Herbst
  Stanford University
  ,
- Byong Chan Lim
  Stanford University
  ,
- Mark Horowitz
  Stanford University
2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)•November 2018, pp 1-8• https://doi.org/10.1145/3240765.3240808
In this paper, we propose an architecture for FPGA emulation of mixed-signal systems that achieves high accuracy at a high throughput. We represent the analog output of a block as a superposition of step responses to changes in its analog input, and the ...
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TETRIS: Scalable and Efficient Neural Network Acceleration with 3D Memory
- Mingyu Gao
  Stanford University, Stanford, CA, USA
  ,
- Jing Pu
  Stanford University, Stanford, CA, USA
  ,
- Xuan Yang
  Stanford University, Stanford, CA, USA
  ,
- Mark Horowitz
  Stanford University, Stanford, CA, USA
  ,
- Christos Kozyrakis
  Stanford University, Stanford, CA, USA
ASPLOS '17: Proceedings of the Twenty-Second International Conference on Architectural Support for Programming Languages and Operating Systems•April 2017, pp 751-764• https://doi.org/10.1145/3037697.3037702

The high accuracy of deep neural networks (NNs) has led to the development of NN accelerators that improve performance by two orders of magnitude. However, scaling these accelerators for higher performance with increasingly larger NNs exacerbates the ...
Also Published in:
ACM SIGPLAN Notices: Volume 52 Issue 4, April 2017ACM SIGARCH Computer Architecture News: Volume 45 Issue 1, March 2017
259Citation
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Improving energy efficiency of DRAM by exploiting half page row access
- Heonjae Ha
  Stanford University
  ,
- Ardavan Pedram
  Stanford University and Movidius
  ,
- Stephen Richardson
  Stanford University
  ,
- Shahar Kvatinsky
  Technion - Israel Institute of Technology
  ,
- Mark Horowitz
  Stanford University
MICRO-49: The 49th Annual IEEE/ACM International Symposium on Microarchitecture•October 2016, Article No.: 27, pp 1-12

DRAM energy is an important component to optimize in modern computing systems. One outstanding source of DRAM energy is the energy to fetch data stored on cells to the row buffer, which occurs during two DRAM operations, row activate and refresh. This ...
1Citation
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Rigel: flexible multi-rate image processing hardware
- James Hegarty
  Stanford University
  ,
- Ross Daly
  Stanford University
  ,
- Zachary DeVito
  Stanford University
  ,
- Jonathan Ragan-Kelley
  Stanford University
  ,
- Mark Horowitz
  Stanford University
  ,
- Pat Hanrahan
  Stanford University
ACM Transactions on Graphics, Volume 35, Issue 4•July 2016, Article No.: 85, pp 1-11 • https://doi.org/10.1145/2897824.2925892

Image processing algorithms implemented using custom hardware or FPGAs of can be orders-of-magnitude more energy efficient and performant than software. Unfortunately, converting an algorithm by hand to a hardware description language suitable for ...
44Citation
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EIE: efficient inference engine on compressed deep neural network
- Song Han
  Stanford University
  ,
- Xingyu Liu
  Stanford University
  ,
- Huizi Mao
  Stanford University
  ,
- Jing Pu
  Stanford University
  ,
- Ardavan Pedram
  Stanford University
  ,
- Mark A. Horowitz
  Stanford University
  ,
- William J. Dally
  Stanford University and NVIDIA
ISCA '16: Proceedings of the 43rd International Symposium on Computer Architecture•June 2016, pp 243-254• https://doi.org/10.1109/ISCA.2016.30

State-of-the-art deep neural networks (DNNs) have hundreds of millions of connections and are both computationally and memory intensive, making them difficult to deploy on embedded systems with limited hardware resources and power budgets. While custom ...
Also Published in:
ACM SIGARCH Computer Architecture News: Volume 44 Issue 3, June 2016
1,291Citation
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extended-abstract
CESEL: Securing a Mote for 20 Years
- Kevin Kiningham
  Stanford University
  ,
- Mark Horowitz
  Stanford University
  ,
- Philip Levis
  Stanford University
  ,
- Dan Boneh
  Stanford University
EWSN '16: Proceedings of the 2016 International Conference on Embedded Wireless Systems and Networks•February 2016, pp 307-312

Embedded wireless sensors, once deployed, may remain in active use for decades. At the same time, as motes come to dominate both the number of hosts and data traffic of the Internet, their security will become fundamental to general Internet security. ...
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demonstration
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Demo: Tethys -- An Energy Harvesting Networked Water Flow Sensor
- Holly Chiang
  Stanford University, Stanford, CA, USA
  ,
- James Hong
  Stanford University, Stanford, CA, USA
  ,
- Kevin Kiningham
  Stanford University, Stanford, CA, USA
  ,
- Jiaqi Xue
  Stanford University, Stanford, USA
  ,
- Laurynas Riliskis
  Stanford University, Stanford, CA, USA
  ,
- Philip Levis
  Stanford University, Stanford, CA, USA
  ,
- Mark Horowitz
  Stanford University, Stanford, CA, USA
SenSys '15: Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems•November 2015, pp 489-490• https://doi.org/10.1145/2809695.2817868

We describe Tethys, an energy-harvesting wireless water flow sensor that can monitor water use at a per-fixture level with the intention of associating water use with specific individuals. Tethys was motivated by recent efforts at Stanford University to ...
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Convolution engine: balancing efficiency and flexibility in specialized computing
- Wajahat Qadeer
  Palo Alto, CA
  ,
- Rehan Hameed
  Palo Alto, CA
  ,
- Ofer Shacham
  Google, Mountain View, CA
  ,
- Preethi Venkatesan
  Intel Corporation, Santa Clara, CA
  ,
- Christos Kozyrakis
  Stanford University, Stanford, CA
  ,
- Mark Horowitz
  Stanford University, Stanford, CA
Communications of the ACM, Volume 58, Issue 4•April 2015, pp 85-93 • https://doi.org/10.1145/2735841

General-purpose processors, while tremendously versatile, pay a huge cost for their flexibility by wasting over 99% of the energy in programmability overheads. We observe that reducing this waste requires tuning data storage and compute structures and ...
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Darkroom: compiling high-level image processing code into hardware pipelines
- James Hegarty
  Stanford University
  ,
- John Brunhaver
  Stanford University
  ,
- Zachary DeVito
  Stanford University
  ,
- Jonathan Ragan-Kelley
  MIT CSAIL
  ,
- Noy Cohen
  Stanford University
  ,
- Steven Bell
  Stanford University
  ,
- Artem Vasilyev
  Stanford University
  ,
- Mark Horowitz
  Stanford University
  ,
- Pat Hanrahan
  Stanford University
ACM Transactions on Graphics, Volume 33, Issue 4•July 2014, Article No.: 144, pp 1-11 • https://doi.org/10.1145/2601097.2601174

Specialized image signal processors (ISPs) exploit the structure of image processing pipelines to minimize memory bandwidth using the architectural pattern of line-buffering, where all intermediate data between each stage is stored in small on-chip ...
111Citation
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Design principles for packet parsers
- Glen Gibb
  Stanford University, Stanford, USA
  ,
- George Varghese
  Microsoft Research, Mountain View, USA
  ,
- Mark Horowitz
  Stanford University, Stanford, USA
  ,
- Nick McKeown
  Stanford University, Stanford, USA
ANCS '13: Proceedings of the ninth ACM/IEEE symposium on Architectures for networking and communications systems•October 2013, pp 13-24

All network devices must parse packet headers to decide how packets should be processed. A 64 x 10Gb/s Ethernet switch must parse one billion packets per second to extract fields used in forwarding decisions. Although a necessary part of all switch ...
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Forwarding metamorphosis: fast programmable match-action processing in hardware for SDN
- Pat Bosshart
  Texas Instruments, Dallas, TX, USA
  ,
- Glen Gibb
  Stanford University, Stanford, CA, USA
  ,
- Hun-Seok Kim
  Texas Instruments, Dallas, TX, USA
  ,
- George Varghese
  Microsoft Research, Mountain View, CA, USA
  ,
- Nick McKeown
  Stanford University, Stanford, CA, USA
  ,
- Martin Izzard
  Texas Instruments, Dallas, TX, USA
  ,
- Fernando Mujica
  Texas Instruments, Dallas, TX, USA
  ,
- Mark Horowitz
  Stanford University, Stanford, CA, USA
SIGCOMM '13: Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM•August 2013, pp 99-110• https://doi.org/10.1145/2486001.2486011

In Software Defined Networking (SDN) the control plane is physically separate from the forwarding plane. Control software programs the forwarding plane (e.g., switches and routers) using an open interface, such as OpenFlow. This paper aims to overcomes ...
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ACM SIGCOMM Computer Communication Review: Volume 43 Issue 4, October 2013
669Citation
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Author Profile Pages

Description: The Author Profile Page initially collects all the professional information known about authors from the publications record as known by the ACM bibliographic database, the Guide. Coverage of ACM publications is comprehensive from the 1950's. Coverage of other publishers generally starts in the mid 1980's. The Author Profile Page supplies a quick snapshot of an author's contribution to the field and some rudimentary measures of influence upon it. Over time, the contents of the Author Profile page may expand at the direction of the community.
Please see the following 2007 Turing Award winners' profiles as examples:
History: Disambiguation of author names is of course required for precise identification of all the works, and only those works, by a unique individual. Of equal importance to ACM, author name normalization is also one critical prerequisite to building accurate citation and download statistics. For the past several years, ACM has worked to normalize author names, expand reference capture, and gather detailed usage statistics, all intended to provide the community with a robust set of publication metrics. The Author Profile Pages reveal the first result of these efforts.
Normalization: ACM uses normalization algorithms to weigh several types of evidence for merging and splitting names.
These include:
- co-authors: if we have two names and cannot disambiguate them based on name alone, then we see if they have a co-author in common. If so, this weighs towards the two names being the same person.
- affiliations: names in common with same affiliation weighs toward the two names being the same person.
- publication title: names in common whose works are published in same journal weighs toward the two names being the same person.
- keywords: names in common whose works address the same subject matter as determined from title and keywords, weigh toward being the same person.
The more conservative the merging algorithms, the more bits of evidence are required before a merge is made, resulting in greater precision but lower recall of works for a given Author Profile. Many bibliographic records have only author initials. Many names lack affiliations. With very common family names, typical in Asia, more liberal algorithms result in mistaken merges.

Automatic normalization of author names is not exact. Hence it is clear that manual intervention based on human knowledge is required to perfect algorithmic results. ACM is meeting this challenge, continuing to work to improve the automated merges by tweaking the weighting of the evidence in light of experience.
Bibliometrics: In 1926, Alfred Lotka formulated his power law (known as Lotka's Law) describing the frequency of publication by authors in a given field. According to this bibliometric law of scientific productivity, only a very small percentage (~6%) of authors in a field will produce more than 10 articles while the majority (perhaps 60%) will have but a single article published. With ACM's first cut at author name normalization in place, the distribution of our authors with 1, 2, 3..n publications does not match Lotka's Law precisely, but neither is the distribution curve far off. For a definition of ACM's first set of publication statistics, see Bibliometrics
Future Direction: The initial release of the Author Edit Screen is open to anyone in the community with an ACM account, but it is limited to personal information. An author's photograph, a Home Page URL, and an email may be added, deleted or edited. Changes are reviewed before they are made available on the live site.
ACM will expand this edit facility to accommodate more types of data and facilitate ease of community participation with appropriate safeguards. In particular, authors or members of the community will be able to indicate works in their profile that do not belong there and merge others that do belong but are currently missing.

A direct search interface for Author Profiles will be built.

An institutional view of works emerging from their faculty and researchers will be provided along with a relevant set of metrics.

It is possible, too, that the Author Profile page may evolve to allow interested authors to upload unpublished professional materials to an area available for search and free educational use, but distinct from the ACM Digital Library proper. It is hard to predict what shape such an area for user-generated content may take, but it carries interesting potential for input from the community.

Bibliometrics

The ACM DL is a comprehensive repository of publications from the entire field of computing.

It is ACM's intention to make the derivation of any publication statistics it generates clear to the user.

Average citations per article = The total Citation Count divided by the total Publication Count.
Citation Count = cumulative total number of times all authored works by this author were cited by other works within ACM's bibliographic database. Almost all reference lists in articles published by ACM have been captured. References lists from other publishers are less well-represented in the database. Unresolved references are not included in the Citation Count. The Citation Count is citations TO any type of work, but the references counted are only FROM journal and proceedings articles. Reference lists from books, dissertations, and technical reports have not generally been captured in the database. (Citation Counts for individual works are displayed with the individual record listed on the Author Page.)
Publication Count = all works of any genre within the universe of ACM's bibliographic database of computing literature of which this person was an author. Works where the person has role as editor, advisor, chair, etc. are listed on the page but are not part of the Publication Count.
Publication Years = the span from the earliest year of publication on a work by this author to the most recent year of publication of a work by this author captured within the ACM bibliographic database of computing literature (The ACM Guide to Computing Literature, also known as "the Guide".
Available for download = the total number of works by this author whose full texts may be downloaded from an ACM full-text article server. Downloads from external full-text sources linked to from within the ACM bibliographic space are not counted as 'available for download'.
Average downloads per article = The total number of cumulative downloads divided by the number of articles (including multimedia objects) available for download from ACM's servers.
Downloads (cumulative) = The cumulative number of times all works by this author have been downloaded from an ACM full-text article server since the downloads were first counted in May 2003. The counts displayed are updated monthly and are therefore 0-31 days behind the current date. Robotic activity is scrubbed from the download statistics.
Downloads (12 months) = The cumulative number of times all works by this author have been downloaded from an ACM full-text article server over the last 12-month period for which statistics are available. The counts displayed are usually 1-2 weeks behind the current date. (12-month download counts for individual works are displayed with the individual record.)
Downloads (6 weeks) = The cumulative number of times all works by this author have been downloaded from an ACM full-text article server over the last 6-week period for which statistics are available. The counts displayed are usually 1-2 weeks behind the current date. (6-week download counts for individual works are displayed with the individual record.)

ACM Author-Izer Service

Summary Description

ACM Author-Izer is a unique service that enables ACM authors to generate and post links on both their homepage and institutional repository for visitors to download the definitive version of their articles from the ACM Digital Library at no charge.

Downloads from these sites are captured in official ACM statistics, improving the accuracy of usage and impact measurements. Consistently linking to definitive version of ACM articles should reduce user confusion over article versioning.

ACM Author-Izer also extends ACM’s reputation as an innovative “Green Path” publisher, making ACM one of the first publishers of scholarly works to offer this model to its authors.

To access ACM Author-Izer, authors need to establish a free ACM web account. Should authors change institutions or sites, they can utilize the new ACM service to disable old links and re-authorize new links for free downloads from a different site.

How ACM Author-Izer Works

Authors may post ACM Author-Izer links in their own bibliographies maintained on their website and their own institution’s repository. The links take visitors to your page directly to the definitive version of individual articles inside the ACM Digital Library to download these articles for free.

The Service can be applied to all the articles you have ever published with ACM.

Depending on your previous activities within the ACM DL, you may need to take up to three steps to use ACM Author-Izer.

For authors who do not have a free ACM Web Account:

Go to the ACM DL http://dl.acm.org/ and click SIGN UP. Once your account is established, proceed to next step.

For authors who have an ACM web account, but have not edited their ACM Author Profile page:

Sign in to your ACM web account and go to your Author Profile page. Click "Add personal information" and add photograph, homepage address, etc. Click ADD AUTHOR INFORMATION to submit change. Once you receive email notification that your changes were accepted, you may utilize ACM Author-izer.

For authors who have an account and have already edited their Profile Page:

Sign in to your ACM web account, go to your Author Profile page in the Digital Library, look for the ACM Author-izer link below each ACM published article, and begin the authorization process. If you have published many ACM articles, you may find a batch Authorization process useful. It is labeled: "Export as: ACM Author-Izer Service"

ACM Author-Izer also provides code snippets for authors to display download and citation statistics for each “authorized” article on their personal pages. Downloads from these pages are captured in official ACM statistics, improving the accuracy of usage and impact measurements. Consistently linking to the definitive version of ACM articles should reduce user confusion over article versioning.

Note: You still retain the right to post your author-prepared preprint versions on your home pages and in your institutional repositories with DOI pointers to the definitive version permanently maintained in the ACM Digital Library. But any download of your preprint versions will not be counted in ACM usage statistics. If you use these AUTHOR-IZER links instead, usage by visitors to your page will be recorded in the ACM Digital Library and displayed on your page.

FAQ

Q. What is ACM Author-Izer?
A. ACM Author-Izer is a unique, link-based, self-archiving service that enables ACM authors to generate and post links on either their home page or institutional repository for visitors to download the definitive version of their articles for free.
Q. What articles are eligible for ACM Author-Izer?
A. ACM Author-Izer can be applied to all the articles authors have ever published with ACM. It is also available to authors who will have articles published in ACM publications in the future.

Q. Are there any restrictions on authors to use this service?
A. No. An author does not need to subscribe to the ACM Digital Library nor even be a member of ACM.

Q. What are the requirements to use this service?
A. To access ACM Author-Izer, authors need to have a free ACM web account, must have an ACM Author Profile page in the Digital Library, and must take ownership of their Author Profile page.

Q. What is an ACM Author Profile Page?
A. The Author Profile Page initially collects all the professional information known about authors from the publications record as known by the ACM Digital Library. The Author Profile Page supplies a quick snapshot of an author's contribution to the field and some rudimentary measures of influence upon it. Over time, the contents of the Author Profile page may expand at the direction of the community. Please visit the ACM Author Profile documentation page for more background information on these pages.

Q. How do I find my Author Profile page and take ownership?
A. You will need to take the following steps:
- Create a free ACM Web Account
- Sign-In to the ACM Digital Library
- Find your Author Profile Page by searching the ACM Digital Library for your name
- Find the result you authored (where your author name is a clickable link)
- Click on your name to go to the Author Profile Page
- Click the "Add Personal Information" link on the Author Profile Page
- Wait for ACM review and approval; generally less than 24 hours

Q. Why does my photo not appear?
A. Make sure that the image you submit is in .jpg or .gif format and that the file name does not contain special characters

Q. What if I cannot find the Add Personal Information function on my author page?
A. The ACM account linked to your profile page is different than the one you are logged into. Please logout and login to the account associated with your Author Profile Page.

Q. What happens if an author changes the location of his bibliography or moves to a new institution?
A. Should authors change institutions or sites, they can utilize ACM Author-Izer to disable old links and re-authorize new links for free downloads from a new location.

Q. What happens if an author provides a URL that redirects to the author’s personal bibliography page?
A. The service will not provide a free download from the ACM Digital Library. Instead the person who uses that link will simply go to the Citation Page for that article in the ACM Digital Library where the article may be accessed under the usual subscription rules.

However, if the author provides the target page URL, any link that redirects to that target page will enable a free download from the Service.

Q. What happens if the author’s bibliography lives on a page with several aliases?
A. Only one alias will work, whichever one is registered as the page containing the author’s bibliography. ACM has no technical solution to this problem at this time.

Q. Why should authors use ACM Author-Izer?
A. ACM Author-Izer lets visitors to authors’ personal home pages download articles for no charge from the ACM Digital Library. It allows authors to dynamically display real-time download and citation statistics for each “authorized” article on their personal site.

Q. Does ACM Author-Izer provide benefits for authors?
A. Downloads of definitive articles via Author-Izer links on the authors’ personal web page are captured in official ACM statistics to more accurately reflect usage and impact measurements.

Authors who do not use ACM Author-Izer links will not have downloads from their local, personal bibliographies counted. They do, however, retain the existing right to post author-prepared preprint versions on their home pages or institutional repositories with DOI pointers to the definitive version permanently maintained in the ACM Digital Library.

Q. How does ACM Author-Izer benefit the computing community?
A. ACM Author-Izer expands the visibility and dissemination of the definitive version of ACM articles. It is based on ACM’s strong belief that the computing community should have the widest possible access to the definitive versions of scholarly literature. By linking authors’ personal bibliography with the ACM Digital Library, user confusion over article versioning should be reduced over time.

In making ACM Author-Izer a free service to both authors and visitors to their websites, ACM is emphasizing its continuing commitment to the interests of its authors and to the computing community in ways that are consistent with its existing subscription-based access model.

Q. How do authors access ACM Author-Izer?
A. See How to Use

Q. Why can’t I find my most recent publication in my ACM Author Profile Page?
A. There is a time delay between publication and the process which associates that publication with an Author Profile Page. Right now, that process usually takes 4-8 weeks.

Q. How does ACM Author-Izer expand ACM’s “Green Path” Access Policies?
A. ACM Author-Izer extends the rights and permissions that authors retain even after copyright transfer to ACM, which has been among the “greenest” publishers. ACM enables its author community to retain a wide range of rights related to copyright and reuse of materials. They include:
- Posting rights that ensure free access to their work outside the ACM Digital Library and print publications
- Rights to reuse any portion of their work in new works that they may create
- Copyright to artistic images in ACM’s graphics-oriented publications that authors may want to exploit in commercial contexts
- All patent rights, which remain with the original owner

Mark Horowitz

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Author Profile Pages

Bibliometrics

ACM Author-Izer Service

Summary Description

How ACM Author-Izer Works

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