The Morning Paper
MAY 14, 2019
Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., A DNN model is trained to recognise patterns in space and time that lead to QoS violations. E.g., in memcached there are five main internal stages, each of which has a hardware or software queue associated with it.
ACM Sigarch
MAY 31, 2023
Heterogeneous and Composable Memory (HCM) offers a feasible solution for terabyte- or petabyte-scale systems, addressing the performance and efficiency demands of emerging big-data applications. About CXL hardware availability with academia. Also, besides the hardware, we see the software ecosystem starts to appear (e.g.,
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Scalegrid
MAY 13, 2020
Greenplum Database is an open-source , hardware-agnostic MPP database for analytics, based on PostgreSQL and developed by Pivotal who was later acquired by VMware. Greenplum’s high performance eliminates the challenge most RDBMS have scaling to petabtye levels of data, as they are able to scale linearly to efficiently process data.
O'Reilly
SEPTEMBER 19, 2023
Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” ” They weren’t quite sure what this “data” substance was, but they’d convinced themselves that they had tons of it that they could monetize.
The Netflix TechBlog
APRIL 29, 2019
Such applications track the inventory of our network gear: what devices, of which models, with which hardware components, located in which sites. We also use Python to detect sensitive data using Lanius. These libraries are the primary way users interface programmatically with work in the Big Data platform.
All Things Distributed
DECEMBER 12, 2018
We also provided web-based training, self-paced labs, customer support, third-party offers, and up to $100,000 in AWS service credits–all at no charge. The first platform is a real time, big data platform being used for analyzing traffic usage patterns to identify congestion and connectivity issues.
All Things Distributed
NOVEMBER 30, 2016
automatic speech recognition, natural language understanding, image classification), collect and clean the training data, and train and tune the machine learning models. Effectively applying AI involves extensive manual effort to develop and tune many different types of machine learning and deep learning algorithms (e.g.
Expert insights. Personalized for you.
45 
Let's personalize your content