NDLI: Language, compiler, and runtime system support towards highly scalable big data application (invited talk abstract)

Please wait, while we are loading the content...

Intent fuzzer: crafting intents of death

Automated test generation for API proxy code (invited talk abstract)

Usable program analysis at google-scale (invited talk abstract)

P: a domain-specific language for asynchronous event-driven programming (invited talk abstract)

Effective race detection for event-driven programs (invited talk abstract)

On the probabilistic analysis of software (invited talk abstract)

Context-sensitive delta inference for identifying workload-dependent performance bottlenecks (invited talk abstract)

Detecting and repairing performance bugs using execution and code patterns (invited talk abstract)

Language, compiler, and runtime system support towards highly scalable big data application (invited talk abstract)

Improving energy efficiency of work-stealing parallel languages (invited talk abstract)

Language, compiler, and runtime system support towards highly scalable big data application (invited talk abstract)

Content Provider	ACM Digital Library
Author	Xu, Guoqing
Abstract	Modern computing has entered the era of Big Data. Analyzing data from Twitter, Google, Facebook, Wikipedia, or the Human Genome Project requires the development of scalable platforms that can quickly extract useful information from an ocean of records collected from customers, clinical trial participants, program execution logs, or the Internet. Most of the existing Big Data applications, including Hadoop, Giraph, Hive, Pig, Mahout, or Hyracks are written managed, object-oriented languages such as Java. While the use of such languages simplifies development tasks, the (memory and execution) inefficiencies inherent in these languages can have large impact on the application performance and scalability. When object-orientation meets Big Data, performance problems are significantly magnified, making data-intensive computing systems fail to scale to large datasets. I will talk about several projects we are currently working on to scale Big Data applications by reducing the cost of a managed runtime. Particularly, I will talk about Facade, a compiler and runtime system we have developed to transform a Big Data application into an almost object-bounded application which has been shown to be much more efficient and scale to much larger datasets. I will also briefly mention two other projects, one attempting to provide a memory-oblivious programming model for developers to allow them to write a program without worrying about how to create threads and use memory, and second aiming to trim a big dataset with probabilistic guarantees to facilitate debugging/testing of a Big Data application. .
Starting Page	13
Ending Page	13
Page Count	1
File Format	PDF
ISBN	9781450329347
DOI	10.1145/2632168.2638835
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-07-22
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Highly scalable big data application System support
Content Type	Text
Resource Type	Article

Central Library (ISO-9001:2015 Certified)
Indian Institute of Technology Kharagpur
Kharagpur, West Bengal, India | PIN - 721302

See location in the Map
03222 282435
Mail: support@ndl.gov.in

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in