In-depth Analysis On Parallel Processing Patterns for High-Performance Dataframes
The Data Science domain has expanded monumentally in both research and industry communities during the past decade, predominantly owing to the Big Data revolution. Artificial Intelligence (AI) and...
Supercharging Distributed Computing Environments For High Performance Data Engineering
The data engineering and data science community has embraced the idea of using Python & R dataframes for regular applications. Driven by the big data revolution and artificial intelligence, these...
Hybrid Cloud and HPC Approach to High-Performance Dataframes
Data pre-processing is a fundamental component in any data-driven application. With the increasing complexity of data processing operations and volume of data, Cylon, a distributed dataframe...
High Performance Dataframes from Parallel Processing Patterns
The data science community today has embraced the concept of Dataframes as the de facto standard for data representation and manipulation. Ease of use, massive operator coverage, and...
HPTMT: Operator-Based Architecture for Scalable High-Performance Data-Intensive Frameworks
Data-intensive applications impact many domains, and their steadily increasing size and complexity demands high-performance, highly usable environments. We integrate a set of ideas developed in...
High Performance Data Engineering Everywhere
The amazing advances being made in the fields of machine and deep learning are a highlight of the Big Data era for both enterprise and research communities. Modern applications require resources...
Data Engineering for HPC with Python
Data engineering is becoming an increasingly important part of scientific discoveries with the adoption of deep learning and machine learning. Data engineering deals with a variety of data...
HPTMT Parallel Operators for High Performance Data Science & Data Engineering
Data-intensive applications are becoming commonplace in all science disciplines. They are comprised of a rich set of sub-domains such as data engineering, deep learning, and machine learning....
A Fast, Scalable, Universal Approach For Distributed Data Aggregations
In the current era of Big Data, data engineering has transformed into an essential field of study across many branches of science. Advancements in Artificial Intelligence (AI) have broadened the...
HPTMT: Operator-Based Architecture for Scalable High-Performance Data-Intensive Frameworks
Deep RC: A Scalable Data Engineering and Deep Learning Pipeline
Significant obstacles exist in scientific domains including genetics, climate modeling, and astronomy due to the management, preprocess, and training on complicated data for deep learning. Even...