Bidirectional Transformations: A Cross-Discipline Perspective: GRACE Meeting Notes, State of the Art, and Outlook

K Czarnecki, JN Foster, Z Hu, R Lämmel… - Theory and Practice of …, 2009 - Springer
Abstract The GRACE International Meeting on Bidirectional Transformations was held in
December 2008 near Tokyo, Japan. The meeting brought together researchers and …

A summary of research on blockchain in the field of intellectual property

J Wang, S Wang, J Guo, Y Du, S Cheng, X Li - Procedia computer science, 2019 - Elsevier
With the continuous development and application of blockchain technology, the academic
and commercial circles are constantly exploring the research directions and practical …

Apache calcite: A foundational framework for optimized query processing over heterogeneous data sources

E Begoli, J Camacho-Rodríguez, J Hyde… - Proceedings of the …, 2018 - dl.acm.org
Apache Calcite is a foundational software framework that provides query processing,
optimization, and query language support to many popular open-source data processing …

Pivot tracing: Dynamic causal monitoring for distributed systems

J Mace, R Roelke, R Fonseca - ACM Transactions on Computer Systems …, 2018 - dl.acm.org
Monitoring and troubleshooting distributed systems is notoriously difficult; potential problems
are complex, varied, and unpredictable. The monitoring and diagnosis tools commonly used …

A comparison of approaches to large-scale data analysis

A Pavlo, E Paulson, A Rasin, DJ Abadi… - Proceedings of the …, 2009 - dl.acm.org
There is currently considerable enthusiasm around the MapReduce (MR) paradigm for large-
scale data analysis [17]. Although the basic control flow of this framework has existed in …

Conclave: secure multi-party computation on big data

N Volgushev, M Schwarzkopf, B Getchell… - Proceedings of the …, 2019 - dl.acm.org
Secure Multi-Party Computation (MPC) allows mutually distrusting parties to run joint
computations without revealing private data. Current MPC algorithms scale poorly with data …

FlumeJava: easy, efficient data-parallel pipelines

C Chambers, A Raniwala, F Perry, S Adams… - ACM Sigplan …, 2010 - dl.acm.org
MapReduce and similar systems significantly ease the task of writing data-parallel code.
However, many real-world computations require a pipeline of MapReduces, and …

tf. data: A machine learning data processing framework

DG Murray, J Simsa, A Klimovic, I Indyk - ar** high-performance software is a difficult task that requires the use of low-level,
architecture-specific programming models (eg, OpenMP for CMPs, CUDA for GPUs, MPI for …

{PRETZEL}: Opening the black box of machine learning prediction serving systems

Y Lee, A Scolari, BG Chun, MD Santambrogio… - … USENIX Symposium on …, 2018 - usenix.org
Machine Learning models are often composed of pipelines of transformations. While this
design allows to efficiently execute single model components at training time, prediction …