822 citations · 950 across the 19 of their papers we have counts for
19 papers
Simpli-Squared: A Very Simple Yet Unexpectedly Powerful Join Ordering Algorithm Without Cardinality Estimates
Asoke Datta, Yesdaulet Izenov, Brian Tsan +1
The Join Order Benchmark (JOB) has become the de facto standard to assess the performance of relational database query optimizers due to its complexity and completeness. In order t…
Adaptive Elastic Training for Sparse Deep Learning on Heterogeneous Multi-GPU Servers
Yujing Ma, Florin Rusu, Kesheng Wu +1
Motivated by extreme multi-label classification applications, we consider training deep learning models over sparse data in multi-GPU servers. The variance in the number of non-zer…
Online Sketch-based Query Optimization
Yesdaulet Izenov, Asoke Datta, Florin Rusu +1
Cost-based query optimization remains a critical task in relational databases even after decades of research and industrial development. Query optimizers rely on a large range of s…
DJEnsemble: On the Selection of a Disjoint Ensemble of Deep Learning Black-Box Spatio-Temporal Models
Yania Molina Souto, Rafael Pereira, Rocío Zorrilla +6
In this paper, we present a cost-based approach for the automatic selection and allocation of a disjoint ensemble of black-box predictors to answer predictive spatio-temporal queri…
Heterogeneous CPU+GPU Stochastic Gradient Descent Algorithms
Yujing Ma, Florin Rusu
The widely-adopted practice is to train deep learning models with specialized hardware accelerators, e.g., GPUs or TPUs, due to their superior performance on linear algebra operati…
In-Depth Benchmarking of Graph Database Systems with the Linked Data Benchmark Council (LDBC) Social Network Benchmark (SNB)
Florin Rusu, Zhiyi Huang
In this study, we present the first results of a complete implementation of the LDBC SNB benchmark -- interactive short, interactive complex, and business intelligence -- in two na…
Exact Selectivity Computation for Modern In-Memory Database Query Optimization
Jun Hyung Shin, Florin Rusu, Alex Suhan
Selectivity estimation remains a critical task in query optimization even after decades of research and industrial development. Optimizers rely on accurate selectivities when gener…
Progressive Data Science: Potential and Challenges
Cagatay Turkay, Nicola Pezzotti, Carsten Binnig +7
Data science requires time-consuming iterative manual activities. In particular, activities such as data selection, preprocessing, transformation, and mining, highly depend on iter…
Distributed Caching for Complex Querying of Raw Arrays
Weijie Zhao, Florin Rusu, Bin Dong +3
As applications continue to generate multi-dimensional data at exponentially increasing rates, fast analytics to extract meaningful results is becoming extremely important. The dat…
Stochastic Gradient Descent on Highly-Parallel Architectures
Yujing Ma, Florin Rusu, Martin Torres
There is an increased interest in building data analytics frameworks with advanced algebraic capabilities both in industry and academia. Many of these frameworks, e.g., TensorFlow…
iPTF Archival Search for Fast Optical Transients
A. Y. Q. Ho, S. R. Kulkarni, P. E. Nugent +18
There has been speculation of a class of relativistic explosions with an initial Lorentz factor smaller than that of classical Gamma-Ray Bursts (GRBs). These "dirty fireballs" woul…
Illuminating Gravitational Waves: A Concordant Picture of Photons from a Neutron Star Merger
M. M. Kasliwal, E. Nakar, L. P. Singer +78
Merging neutron stars offer an exquisite laboratory for simultaneously studying strong-field gravity and matter in extreme environments. We establish the physical association of an…
OLA-RAW: Scalable Exploration over Raw Data
Yu Cheng, Weijie Zhao, Florin Rusu
In-situ processing has been proposed as a novel data exploration solution in many domains generating massive amounts of raw data, e.g., astronomy, since it provides immediate SQL q…
Dot-Product Join: An Array-Relation Join Operator for Big Model Analytics
Chengjie Qin, Florin Rusu
Big Model analytics tackles the training of massive models that go beyond the available memory of a single computing device, e.g., CPU or GPU. It generalizes Big Data analytics whi…
Workload-Driven Vertical Partitioning for Effective Query Processing over Raw Data
Weijie Zhao, Yu Cheng, Florin Rusu
Traditional databases are not equipped with the adequate functionality to handle the volume and variety of "Big Data". Strict schema definition and data loading are prerequisites e…
Speculative Approximations for Terascale Analytics
Chengjie Qin, Florin Rusu
Model calibration is a major challenge faced by the plethora of statistical analytics packages that are increasingly used in Big Data applications. Identifying the optimal model pa…
Formal Representation of the SS-DB Benchmark and Experimental Evaluation in EXTASCID
Yu Cheng, Florin Rusu
Evaluating the performance of scientific data processing systems is a difficult task considering the plethora of application-specific solutions available in this landscape and the…
A Survey on Array Storage, Query Languages, and Systems
Florin Rusu, Yu Cheng
Since scientific investigation is one of the most important providers of massive amounts of ordered data, there is a renewed interest in array data processing in the context of Big…
PF-OLA: A High-Performance Framework for Parallel On-Line Aggregation
Chengjie Qin, Florin Rusu
Online aggregation provides estimates to the final result of a computation during the actual processing. The user can stop the computation as soon as the estimate is accurate enoug…