The Digital Library : DL Government Pricing
For Government organizations, subscriptions include access to te entire ACM Digital Library, unlimited concurrent usage and unlimited article downloads, access to the complete archive of the Digital Library, and to The Guide to computing Literature. Government organizations with multi sites can receive a discount based on the number of participating sites for a government organization.
2018 List Price
List Price for Government Institutions (Single Site License): $21,998 US
All Digital Library orders with subscription start date of January 1, 2018 or after will receive 2018 pricing.
2017 List Price
List Price for Government Institutions (Single Site License): $20,950 US
All Digital Library orders with subscription start date of January 1, 2017 or after will receive 2017 pricing.
Written by leading domain experts for software engineers, ACM Case Studies provide an in-depth look at how software teams overcome specific challenges by implementing new technologies, adopting new practices, or a combination of both. Often through first-hand accounts, these pieces explore what the challenges were, the tools and techniques that were used to combat them, and the solution that was achieved.
Why I Belong to ACM
Hear from Bryan Cantrill, vice president of engineering at Joyent, Ben Fried chief information officer at Google, and Theo Schlossnagle, OmniTI founder on why they are members of ACM.
ACM Queue’s “Research for Practice” is your number one resource for keeping up with emerging developments in the world of theory and applying them to the challenges you face on a daily basis. In this installment, Dan Crankshaw and Joey Gonzalez provide an overview of machine learning server systems. What happens when we wish to actually deploy a machine learning model to production, and how do we serve predictions with high accuracy and high computational efficiency? Dan and Joey’s curated research selection presents cutting-edge techniques spanning database-level integration, video processing, and prediction middleware. Given the explosion of interest in machine learning and its increasing impact on seemingly every application vertical, it's possible that systems such as these will become as commonplace as relational databases are today.