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SKP's Java/Java EE Gotchas: Clash of the Titans, C++ vs. Java!

DZone

As a Software Engineer, the mind is trained to seek optimizations in every aspect of development and ooze out every bit of available CPU Resource to deliver a performing application. This begins not only in designing the algorithm or coming out with efficient and robust architecture but right onto the choice of programming language.

Java 207
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What Is a Workload in Cloud Computing

Scalegrid

This article analyzes cloud workloads, delving into their forms, functions, and how they influence the cost and efficiency of your cloud infrastructure. Executing cutting-edge intelligent apps’ deployment after successful training becomes much easier thanks primarily to this functionality made possible! Additionally.

Cloud 130
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Lerner?—?using RL agents for test case scheduling

The Netflix TechBlog

Netflix engineers run a series of tests and benchmarks to validate the device across multiple dimensions including compatibility of the device with the Netflix SDK, device performance, audio-video playback quality, license handling, encryption and security. Likewise it has very low requirements on the initial amount of training data.

Testing 163
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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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Machine learning systems are stuck in a rut

The Morning Paper

Systems researchers are doing an excellent job improving the performance of 5-year old benchmarks, but gradually making it harder to explore innovative machine learning research ideas. Convolutional Capsule primitives can be implemented reasonably efficiently on CPU but problems arise on accelerators (e.g. GPU and TPU).

Systems 87
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Reignite Your SAFe® Journey with Flow Metrics

Tasktop

We must have a deep understanding of what changes will have the biggest impact on velocity, predictability, efficiency, throughput and so on.”. Are they meeting their benchmarks for adoption, are their outcomes improving, are the KPIs different? Flow : How efficient are you at delivering value to customers? “As

Metrics 98
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Progress Delayed Is Progress Denied

Alex Russell

As an engineer on a browser team, I'm privy to the blow-by-blow of various performance projects, benchmark fire drills, and the ways performance marketing (deeply) impacts engineering priorities. With each team, benchmarks lost are understood as bugs. Provides support for "unread counts", e.g. for email and chat programs.

Media 145