# reduction

Published articles for reduction.

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## How tetrahedral cages significantly reduce BVH memory usage

DevFeed: [How tetrahedral cages significantly reduce BVH memory usage](<https://devfeed.tech/articles/how-tetrahedral-cages-significantly-reduce-bvh-memory-usage-41419.md>)

Original publisher: [Read original article](<https://gpuopen.com/learn/how-tetrahedral-cages-significantly-reduce-bvh-memory-usage/>)

Author: Holger Gruen

Published: 2026-09-17T13:00:00Z

Content type: tutorial

Language: en

Sources: [AMD GPUOpen](<https://devfeed.tech/sources/amd-gpuopen.md>)

Topics: [GPU](<https://devfeed.tech/topics/gpu.md>), [Graphics](<https://devfeed.tech/topics/graphics.md>), [Simulation and Design](<https://devfeed.tech/topics/simulation-and-design.md>)

Tags: [animation](<https://devfeed.tech/tags/animation.md>), [article-release](<https://devfeed.tech/tags/article-release.md>), [directx](<https://devfeed.tech/tags/directx.md>), [fps](<https://devfeed.tech/tags/fps.md>), [game-development](<https://devfeed.tech/tags/game-development.md>), [graphics](<https://devfeed.tech/tags/graphics.md>), [graphics-apis](<https://devfeed.tech/tags/graphics-apis.md>), [memory](<https://devfeed.tech/tags/memory.md>), [microsoft-directx](<https://devfeed.tech/tags/microsoft-directx.md>), [optimization](<https://devfeed.tech/tags/optimization.md>), [performance](<https://devfeed.tech/tags/performance.md>), [ray-tracing](<https://devfeed.tech/tags/ray-tracing.md>), [raytracing](<https://devfeed.tech/tags/raytracing.md>), [reduction](<https://devfeed.tech/tags/reduction.md>), [research](<https://devfeed.tech/tags/research.md>), [technical-article](<https://devfeed.tech/tags/technical-article.md>), [technical-articles](<https://devfeed.tech/tags/technical-articles.md>), [white-paper](<https://devfeed.tech/tags/white-paper.md>)

### AI overview

This article explains how tetrahedral cages reduce BVH memory usage and update costs when ray tracing independently animated geometry. In an AMD sample with animated plants, the technique uses about 1.7 GB of BVH memory and approximately 3.3 ms for BVH updates per frame, compared with up to 80 GB and more than 300 ms for conventional dense triangle BLAS updates on a Radeon RX 9070 XT GPU.

### Source excerpt

The AMD tetrahedral cage technique ray traces 25,000 independently animated plants at 60+ FPS while slashing BVH memory and update costs for massive dynamic scenes.

## How Rain Affects Wireless Microwave Links: 24 GHz, 60 GHz, and 80 GHz Compared

DevFeed: [How Rain Affects Wireless Microwave Links: 24 GHz, 60 GHz, and 80 GHz Compared](<https://devfeed.tech/articles/how-rain-affects-wireless-microwave-links-24-ghz-60-ghz-and-80-ghz-compared-40174.md>)

Original publisher: [Read original article](<https://blog.j2sw.com/netops/wireless/rain-fade-microwave-links/>)

Author: j2sw

Published: 2026-06-15T09:47:43Z

Content type: tutorial

Language: en

Sources: [Justin Wilson (j2sw)](<https://devfeed.tech/sources/justin-wilson-j2sw.md>)

Topics: [Network](<https://devfeed.tech/topics/network.md>), [Network design](<https://devfeed.tech/topics/network-design.md>), [Internet](<https://devfeed.tech/topics/internet.md>), [data centers](<https://devfeed.tech/topics/data-centers.md>)

Tags: [24ghz](<https://devfeed.tech/tags/24ghz.md>), [60ghz](<https://devfeed.tech/tags/60ghz.md>), [80ghz](<https://devfeed.tech/tags/80ghz.md>), [adaptive](<https://devfeed.tech/tags/adaptive.md>), [backhaul](<https://devfeed.tech/tags/backhaul.md>), [capacity](<https://devfeed.tech/tags/capacity.md>), [changes](<https://devfeed.tech/tags/changes.md>), [e-band](<https://devfeed.tech/tags/e-band.md>), [error-correction](<https://devfeed.tech/tags/error-correction.md>), [fiber](<https://devfeed.tech/tags/fiber.md>), [microwave](<https://devfeed.tech/tags/microwave.md>), [network](<https://devfeed.tech/tags/network.md>), [network-design](<https://devfeed.tech/tags/network-design.md>), [perfomance](<https://devfeed.tech/tags/perfomance.md>), [radio](<https://devfeed.tech/tags/radio.md>), [reduction](<https://devfeed.tech/tags/reduction.md>), [rf](<https://devfeed.tech/tags/rf.md>), [wireless](<https://devfeed.tech/tags/wireless.md>), [wireless-networking](<https://devfeed.tech/tags/wireless-networking.md>)

### AI overview

This article explains how rain fade affects wireless microwave links, with emphasis on 24 GHz, 60 GHz, and 80 GHz bands. It describes how precipitation reduces signal strength, causes adaptive modulation and throughput reductions, and can eventually cause a link to drop when fade margin is exhausted.

### Source excerpt

Rain can have a major impact on wireless microwave links, especially as frequencies increase. Learn how rain fade affects 24 GHz, 60 GHz, and 80 GHz circuits, and why fade margin is critical for reliable network design. The post How Rain Affects Wireless Microwave Links: 24 GHz, 60 GHz, and 80 GHz Compared appeared first on Justin Wilson (j2sw).

## Using the Frisch-Waugh-Lovell Theorem to Improve CUPED Variance Reduction in Online Experiments

DevFeed: [Using the Frisch-Waugh-Lovell Theorem to Improve CUPED Variance Reduction in Online Experiments](<https://devfeed.tech/articles/you-can-t-spell-cuped-without-frisch-waugh-lovell-37906.md>)

Original publisher: [Read original article](<https://www.evanmiller.org/you-cant-spell-cuped-without-frisch-waugh-lovell.html>)

Author: Evan Miller

Published: 2022-07-15T00:35:00Z

Content type: tutorial

Language: en

Sources: [Evan Miller](<https://devfeed.tech/sources/evan-miller.md>)

Topics: [experiments](<https://devfeed.tech/topics/experiments.md>), [math](<https://devfeed.tech/topics/math.md>), [data](<https://devfeed.tech/topics/data.md>)

Tags: [analysis](<https://devfeed.tech/tags/analysis.md>), [experiments](<https://devfeed.tech/tags/experiments.md>), [math](<https://devfeed.tech/tags/math.md>), [reduction](<https://devfeed.tech/tags/reduction.md>), [variance](<https://devfeed.tech/tags/variance.md>)

### AI overview

This tutorial explains the mathematical connection between CUPED and partial linear regression through the Frisch-Waugh-Lovell Theorem. It discusses how variance reduction can decrease experiment sample sizes and proposes including a vector of treatments in CUPED regressions for additional variance reduction.

### Source excerpt

A/B tests run faster with CUPED. Here I explain the underlying math, and use it to invent an even better variance-reduction technique for online experiments: You Can't Spell CUPED Without Frisch-Waugh-Lovell

## The Halting Problem

DevFeed: [The Halting Problem](<https://devfeed.tech/articles/the-halting-problem-40751.md>)

Original publisher: [Read original article](<https://radek.io/posts/the-halting-problem/>)

Published: 2014-07-27T00:00:00Z

Content type: article

Language: en

Sources: [Radek Pazdera](<https://devfeed.tech/sources/radek-pazdera.md>)

Topics: [Computer science](<https://devfeed.tech/topics/computer-science.md>), [Algorithm](<https://devfeed.tech/topics/algorithm.md>), [Math and Logic](<https://devfeed.tech/topics/math-and-logic.md>)

Tags: [algorithm](<https://devfeed.tech/tags/algorithm.md>), [computer-science](<https://devfeed.tech/tags/computer-science.md>), [computers](<https://devfeed.tech/tags/computers.md>), [halting-problem](<https://devfeed.tech/tags/halting-problem.md>), [infinite](<https://devfeed.tech/tags/infinite.md>), [input](<https://devfeed.tech/tags/input.md>), [logic](<https://devfeed.tech/tags/logic.md>), [loops](<https://devfeed.tech/tags/loops.md>), [program](<https://devfeed.tech/tags/program.md>), [reduction](<https://devfeed.tech/tags/reduction.md>)

### AI overview

The article explains Alan Turing's halting problem: no general method can always determine whether an arbitrary program will halt or run forever. It describes the problem's connection to undecidability, diagonalization, and reductions, and briefly discusses Turing's work with Alonzo Church.

### Source excerpt

And other things computers cannot solve

## A problem that is not (properly) PAC-learnable

DevFeed: [A problem that is not (properly) PAC-learnable](<https://devfeed.tech/articles/a-problem-that-is-not-properly-pac-learnable-40356.md>)

Original publisher: [Read original article](<https://www.jeremykun.com/2014/04/21/an-un-pac-learnable-problem/>)

Published: 2014-04-21T10:00:16Z

Content type: tutorial

Language: en

Sources: [Jeremy Kun](<https://devfeed.tech/sources/jeremy-kun.md>)

Topics: [Learning](<https://devfeed.tech/topics/learning.md>), [math](<https://devfeed.tech/topics/math.md>), [Math and Logic](<https://devfeed.tech/topics/math-and-logic.md>)

Tags: [algorithm](<https://devfeed.tech/tags/algorithm.md>), [boolean](<https://devfeed.tech/tags/boolean.md>), [boolean-satisfiability](<https://devfeed.tech/tags/boolean-satisfiability.md>), [classes](<https://devfeed.tech/tags/classes.md>), [computational-complexity](<https://devfeed.tech/tags/computational-complexity.md>), [computational-learning-theory](<https://devfeed.tech/tags/computational-learning-theory.md>), [learning-theory](<https://devfeed.tech/tags/learning-theory.md>), [logical](<https://devfeed.tech/tags/logical.md>), [math](<https://devfeed.tech/tags/math.md>), [mathematics](<https://devfeed.tech/tags/mathematics.md>), [misconceptions](<https://devfeed.tech/tags/misconceptions.md>), [np](<https://devfeed.tech/tags/np.md>), [np-completeness](<https://devfeed.tech/tags/np-completeness.md>), [pac-learning](<https://devfeed.tech/tags/pac-learning.md>), [reduction](<https://devfeed.tech/tags/reduction.md>), [rp](<https://devfeed.tech/tags/rp.md>)

### AI overview

This technical learning-theory article presents a standard example of a problem that is not learnable under the previously introduced PAC model, then explains how a more expressive hypothesis class changes that result. Its addendum clarifies that 3-term DNF formulas are not shown to be unlearnable under the standard PAC definition, only under the earlier restricted definition.

### Source excerpt

In a previous post we introduced a learning model called Probably Approximately Correct (PAC). We saw an example of a concept class that was easy to learn: intervals on the real line (and more generally, if you did the exercise, axis-aligned rectangles in a fixed dimension). One of the primary goals of studying models of learning is to figure out what is learnable and what is not learnable in the various models.