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Beyond data and model parallelism for deep neural networks

The Morning Paper

Beyond data and model parallelism for deep neural networks Jia et al., The goal here is to reduce the training times of DNNs by finding efficient parallel execution strategies, and even including its search time, FlexFlow is able to increase training throughput by up to 3.3x SysML’2019. Expanding the search space.

Network 81
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Lerner?—?using RL agents for test case scheduling

The Netflix TechBlog

The device ecosystem is rich with partners ranging from Silicon-on-Chip (SoC) manufacturers, Original Design Manufacturer (ODM) and Original Equipment Manufacturer (OEM) vendors. Solving the above problems could help Netflix and our Partners save time and money during the entire lifecycle of device design, build, test, and certification.

Testing 163
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What Is a Workload in Cloud Computing

Scalegrid

This is sometimes referred to as using an “over-cloud” model that involves a centrally managed resource pool that spans all parts of a connected global network with internal connections between regional borders, such as two instances in IAD-ORD for NYC-JS webpage DNS routing. Additionally.

Cloud 130
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Supercomputing Predictions: Custom CPUs, CXL3.0, and Petalith Architectures

Adrian Cockcroft

Here’s some predictions I’m making: Jack Dongarra’s efforts to highlight the low efficiency of the HPCG benchmark as an issue will influence the next generation of supercomputer architectures to optimize for sparse matrix computations. In early January a related paper was published by Satoshi Matsuoka et. petaflops, which is 0.8%

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What Adrian Did Next?—?Part 2?—?Sun Microsystems

Adrian Cockcroft

The early days at Sun Cambridge were special, I absorbed a lot about networking and the technical side of the role from my fellow systems engineer Martin Baines, and we were driving all over the region in cool company cars (I had a Citroen BX 16V) selling a really hot product.

Tuning 52
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The Ultimate Guide to Database High Availability

Percona

Typically, the servers are configured in a primary/replica configuration, with one server designated as the primary server that handles all incoming requests and the others designated as replica servers that monitor the primary and take over its workload if it fails. This flexibility can be crucial in designing a scalable architecture.

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CDN Web Application Firewall (WAF): Your Shield Against Online Threats

IO River

The OSI Model is like a layer cake of how data moves through networks. This means it specifically looks at the content of the data (like the writing inside our letters from the analogy) rather than just the envelope.So, what is the difference between a Firewall at the application level and network level?Network-level

Traffic 52