Data-driven decisions are critical to driving business results. R is a critical tool for data scientists to help organizations derive competitive advantage from their data. TidalScale Software-Defined Servers provide a unique platform for data analysis that delivers a unique combination of in-memory performance, scalability, and cost-effectiveness that assure sustained competitive advantage for your business.
Deploy the memory you need, when you need it to deliver insights quickly.
No complex distributed software development or data partitioning.
Flexibly deploy and re-deploy commodity servers to build systems to fit your data requirements.
TidalScale Software-Defined Servers can be deployed in the Cloud (IaaS) or on-premises.
Don’t be bound by scaling limitations of scale-up systems or the complexity and operational costs of scale-out solutions.
IEEE Revisiting Coherent Shared Memory
IEEE Scaling the Computer to the Problem
Gartner: Guide to Software-Defined Servers in the Data Center
7 Technology Trends Driving the Industry to Software-Defined Servers
TidalScale Open Source R Benchmark
The Economics of Software-Defined Servers
The Wandering CPU
Amdahl vs Gustafson
TidalScale Next Generation Software-Defined Servers
TTI Vanguard’s “Reprogramming Programming” – Ike Nassi
TidalScale: The Machine Learning Layer
TidalScale: Technical Overview
TidalScale: The HyperKernel
Introduction to TidalScale
TidalScale at the UseR Conference
TidalScale at the Open Data Science Conference – A Game Changer for Data Scientists
TidalScale at the Open Data Science Conference – How to Power Through Data Science Problems with Software-Defined Servers
TidalScale Data Science Webinar