# White Paper

Published articles for White Paper.

This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles.

## 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.

## Temporally stable generative illumination with a one-step diffusion model

DevFeed: [Temporally stable generative illumination with a one-step diffusion model](<https://devfeed.tech/articles/temporally-stable-generative-illumination-with-a-one-step-diffusion-model-15050.md>)

Original publisher: [Read original article](<https://gpuopen.com/learn/temporally-stable-generative-illumination/>)

Author: SungYe Kim; Harish Anand; Alexandr Kuznetsov; Wojciech Uss; Wojciech Kaliński; Rama Harihara

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

Content type: article

Language: en

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

Topics: [real-time rendering](<https://devfeed.tech/topics/real-time-rendering.md>), [VAE](<https://devfeed.tech/topics/vae.md>)

Tags: [arr-group](<https://devfeed.tech/tags/arr-group.md>), [article-release](<https://devfeed.tech/tags/article-release.md>), [diffusion](<https://devfeed.tech/tags/diffusion.md>), [generation](<https://devfeed.tech/tags/generation.md>), [gi](<https://devfeed.tech/tags/gi.md>), [inference](<https://devfeed.tech/tags/inference.md>), [lighting](<https://devfeed.tech/tags/lighting.md>), [ml](<https://devfeed.tech/tags/ml.md>), [model](<https://devfeed.tech/tags/model.md>), [optimization](<https://devfeed.tech/tags/optimization.md>), [quality](<https://devfeed.tech/tags/quality.md>), [ray-tracing](<https://devfeed.tech/tags/ray-tracing.md>), [raytracing](<https://devfeed.tech/tags/raytracing.md>), [real-time](<https://devfeed.tech/tags/real-time.md>), [real-time-rendering](<https://devfeed.tech/tags/real-time-rendering.md>), [research](<https://devfeed.tech/tags/research.md>), [white-paper](<https://devfeed.tech/tags/white-paper.md>)

### AI overview

The article presents a single-step latent diffusion method for real-time global illumination. It conditions image generation on scene signals and lighting hints, and uses a Temporal VAE decoder with motion-vector reprojection to improve temporal stability and reduce flicker.

### Source excerpt

A generative method for real-time global illumination using a single-step latent diffusion model, delivering stable, high-quality lighting without costly iterative processing.

## GPU view-adaptive crack-free subdivision of Bézier surfaces

DevFeed: [GPU view-adaptive crack-free subdivision of Bézier surfaces](<https://devfeed.tech/articles/gpu-view-adaptive-crack-free-subdivision-of-bezier-surfaces-15041.md>)

Original publisher: [Read original article](<https://gpuopen.com/learn/gpu-view-adaptive-subdivision/>)

Author: Bastian Kuth; Quirin Meyer

Published: 2026-08-06T12:00:00Z

Content type: tutorial

Language: en

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

Topics: [GPU](<https://devfeed.tech/topics/gpu.md>), [procedural geometry](<https://devfeed.tech/topics/procedural-geometry.md>), [Hardware](<https://devfeed.tech/topics/hardware.md>)

Tags: [adaptive](<https://devfeed.tech/tags/adaptive.md>), [article-release](<https://devfeed.tech/tags/article-release.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [graphics](<https://devfeed.tech/tags/graphics.md>), [graphics-apis](<https://devfeed.tech/tags/graphics-apis.md>), [maths](<https://devfeed.tech/tags/maths.md>), [memory](<https://devfeed.tech/tags/memory.md>), [microsoft-work-graphs](<https://devfeed.tech/tags/microsoft-work-graphs.md>), [optimization](<https://devfeed.tech/tags/optimization.md>), [performance](<https://devfeed.tech/tags/performance.md>), [render](<https://devfeed.tech/tags/render.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>), [techniques](<https://devfeed.tech/tags/techniques.md>), [white-paper](<https://devfeed.tech/tags/white-paper.md>), [work-graphs](<https://devfeed.tech/tags/work-graphs.md>)

### AI overview

This article explains a GPU work graph approach to recursively subdividing bicubic Bézier surfaces. The method adapts triangle density to curvature and camera distance, reducing unnecessary geometry while maintaining crack-free rendering.

### Source excerpt

Learn how fast, crack-free GPU work graph subdivision for bicubic Bézier surfaces dramatically reduce triangle counts while simplifying implementation and matching hardware-tessellation quality.

## Ray tracing massive amounts of animated geometry using tetrahedral cages

DevFeed: [Ray tracing massive amounts of animated geometry using tetrahedral cages](<https://devfeed.tech/articles/ray-tracing-massive-amounts-of-animated-geometry-using-tetrahedral-cages-15048.md>)

Original publisher: [Read original article](<https://gpuopen.com/learn/ray-tracing-massive-amounts-animated-geometry/>)

Author: Holger Gruen

Published: 2026-07-22T01:00:00Z

Content type: article

Language: en

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

Topics: [Ray Tracing](<https://devfeed.tech/topics/ray-tracing.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [real-time](<https://devfeed.tech/topics/real-time.md>)

Tags: [agility-sdk](<https://devfeed.tech/tags/agility-sdk.md>), [animation](<https://devfeed.tech/tags/animation.md>), [architecture](<https://devfeed.tech/tags/architecture.md>), [article-release](<https://devfeed.tech/tags/article-release.md>), [directx](<https://devfeed.tech/tags/directx.md>), [game-development](<https://devfeed.tech/tags/game-development.md>), [gpu](<https://devfeed.tech/tags/gpu.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-agility-sdk](<https://devfeed.tech/tags/microsoft-agility-sdk.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>), [real-time](<https://devfeed.tech/tags/real-time.md>), [research](<https://devfeed.tech/tags/research.md>), [reuse](<https://devfeed.tech/tags/reuse.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

The article explains a ray-tracing method for massive animated scenes that uses low-resolution tetrahedral cages to deform geometry while reusing static mini-meshes and mini-BLASes. This reduces per-frame update and memory costs, with the paper demonstrating roughly 585 million animated triangles at 60 frames per second on an AMD Radeon RX 9070 XT at 1080p.

### Source excerpt

Animate compact tetrahedral cages and reuse static mini-BLASes to ray-trace hundreds of millions of triangles in real time, dramatically cutting per-frame update and memory costs for dense foliage, grass, and crowds.

## MANRS for Enterprise Customers

DevFeed: [MANRS for Enterprise Customers](<https://devfeed.tech/articles/manrs-for-enterprise-customers-11345.md>)

Original publisher: [Read original article](<https://blog.ipspace.net/2026/03/manrs-enterprise/>)

Published: 2026-03-17T07:13:00Z

Content type: opinion

Language: en

Sources: [ipSpace.net blog](<https://devfeed.tech/sources/ipspace-net-blog.md>)

Topics: [Routing Security](<https://devfeed.tech/topics/routing-security.md>), [networking](<https://devfeed.tech/topics/networking.md>), [Security](<https://devfeed.tech/topics/security.md>)

Tags: [blog-post](<https://devfeed.tech/tags/blog-post.md>), [connectivity](<https://devfeed.tech/tags/connectivity.md>), [internet](<https://devfeed.tech/tags/internet.md>), [networking](<https://devfeed.tech/tags/networking.md>), [routing-security](<https://devfeed.tech/tags/routing-security.md>), [security](<https://devfeed.tech/tags/security.md>), [white-paper](<https://devfeed.tech/tags/white-paper.md>)

### AI overview

The article argues that enterprises should use their purchasing power to encourage Internet service providers to adopt MANRS routing-security practices. It highlights limited MANRS participation among providers serving Croatia and Slovenia and points readers to a MANRS white paper about Internet routing as an overlooked enterprise supply-chain dependency.

### Source excerpt

In October 2023, I was talking about Internet routing security at the DEEP conference in Zadar, Croatia. After explaining the (obvious) challenges and the initiatives aimed at making Internet routing more secure (MANRS), I made my usual recommendation: vote with your wallet. However, if you're a company in Croatia (or Slovenia, or a number of other countries), you're stuck. While ISPs in Croatia might be doing a great job, none of them is a MANRS participant1, so we don't know how good they are. The situation is not much better in Slovenia; the only ISPs claiming to serve Slovenia are Anexia (a cloud provider) and Go6 Institute, the small network operated by my good friend (and True Believer in IPv6 and MANRS) Jan Žorž. Moving further north, there are decent choices in Austria, and tons of options in Germany or Switzerland. I must be living in a truly thrifty part of Europe. Read more ...

## White Paper on Data Science Technical Program Management

DevFeed: [White Paper on Data Science Technical Program Management](<https://devfeed.tech/articles/white-paper-on-data-science-technical-program-management-22548.md>)

Original publisher: [Read original article](<https://medium.com/walmartglobaltech/white-paper-on-data-science-technical-program-management-08dc2535bd1a?source=rss----905ea2b3d4d1---4>)

Author: Sonu Jain

Published: 2026-02-27T12:41:46Z

Content type: article

Language: en

Sources: [Walmart Global Tech](<https://devfeed.tech/sources/walmart-global-tech.md>)

Topics: [Data Science](<https://devfeed.tech/topics/data-science.md>), [Model Development](<https://devfeed.tech/topics/model-development.md>), [Development](<https://devfeed.tech/topics/development.md>), [Software Engineering](<https://devfeed.tech/topics/software-engineering.md>)

Tags: [collaboration](<https://devfeed.tech/tags/collaboration.md>), [coverage](<https://devfeed.tech/tags/coverage.md>), [data-science](<https://devfeed.tech/tags/data-science.md>), [experimental](<https://devfeed.tech/tags/experimental.md>), [leadership](<https://devfeed.tech/tags/leadership.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [management](<https://devfeed.tech/tags/management.md>), [paper](<https://devfeed.tech/tags/paper.md>), [retail](<https://devfeed.tech/tags/retail.md>), [software-engineering](<https://devfeed.tech/tags/software-engineering.md>), [technical](<https://devfeed.tech/tags/technical.md>), [technical-program-manager](<https://devfeed.tech/tags/technical-program-manager.md>), [training](<https://devfeed.tech/tags/training.md>), [validation](<https://devfeed.tech/tags/validation.md>), [white-paper](<https://devfeed.tech/tags/white-paper.md>)

### AI overview

This white paper presents a structured approach to managing Data Science programs through technical program management. It discusses business alignment, cross-functional collaboration, data validation, model training and retraining, governance, and phased execution, using an inventory forecasting initiative as a real-world example.

### Source excerpt

1. Abstract Managing Data Science programs requires a structured approach to handle the complexities of data, model development, and business alignment. This whitepaper provides a comprehensive guide on the effective program management of Data Science programs by technical program managers. It highlights the critical role of Technical Program Managers (TPMs) in driving successful execution and outlines the key phases, challenges, and recommended best practices at every stage for effectively managing Data Science programs This white paper is grounded in a real-world inventory forecasting initiative aimed at improving stock availability and reducing overstock across multiple retail categories. The program involved cross-functional collaboration between Data Science, Engineering, Product, and Business teams to build predictive models that could dynamically adjust inventory levels based on demand signals. 2. Introduction Data Science has become a critical pillar of decision-making across industries, but organizations continue to struggle with operationalizing these initiatives. Unlike software development, which follows predictable sprint cycles, Data Science programs are inherently experimental -- requiring repeated cycles of data validation, model training, and retraining before they reach acceptable performance levels. This uncertainty often leads to misaligned expectations, delays in delivery, and inconsistent business impact. The iterative nature of model development makes predictability especially challenging: teams may require multiple iterations to achieve coverage and accuracy thresholds that satisfy business needs. Without structured program management, these efforts risk becoming siloed experiments rather than scalable, value-generating solutions. This whitepaper aims to address this gap by providing a practical framework for Technical Program Managers (TPMs) to manage Data Science programs effectively. It draws on real-world experience from a large-scale inve

## The Jenga View of Threat Modeling

DevFeed: [The Jenga View of Threat Modeling](<https://devfeed.tech/articles/the-jenga-view-of-threat-modeling-37006.md>)

Original publisher: [Read original article](<https://shostack.org/blog/the-jenga-view-of-threat-modeling/>)

Author: Adam

Published: 2020-06-16T00:00:00Z

Content type: release

Language: en

Sources: [Shostack & Friends Blog](<https://devfeed.tech/sources/shostack-friends-blog.md>)

Topics: [Security](<https://devfeed.tech/topics/security.md>), [Application Security](<https://devfeed.tech/topics/application-security.md>)

Tags: [announce](<https://devfeed.tech/tags/announce.md>), [application-security](<https://devfeed.tech/tags/application-security.md>), [paper](<https://devfeed.tech/tags/paper.md>), [teaching](<https://devfeed.tech/tags/teaching.md>), [white-paper](<https://devfeed.tech/tags/white-paper.md>)

### AI overview

Shostack + Associates announces its first corporate white paper, which uses Jenga as a metaphor to explain why threat modeling efforts fail and to discuss the culture and organizational work required for improvement. The paper is released under a Creative Commons license without registration.

### Source excerpt

I'm happy to announce Shostack + Associate's new, first, corporate white paper! It uses Jenga to explain why threat modeling efforts fail so often.

## Cut and try: building a dream

DevFeed: [Cut and try: building a dream](<https://devfeed.tech/articles/cut-and-try-building-a-dream-16746.md>)

Original publisher: [Read original article](<https://blog.ethereum.org/en/2016/02/09/cut-and-try-building-a-dream>)

Author: Taylor Gerring

Published: 2016-02-09T16:16:46Z

Content type: opinion

Language: en

Sources: [Ethereum Foundation Blog](<https://devfeed.tech/sources/ethereum-foundation-blog.md>)

Topics: [Ethereum](<https://devfeed.tech/topics/ethereum.md>), [Blockchain](<https://devfeed.tech/topics/blockchain.md>), [Bitcoin](<https://devfeed.tech/topics/bitcoin.md>)

Tags: [anniversary](<https://devfeed.tech/tags/anniversary.md>), [announcement](<https://devfeed.tech/tags/announcement.md>), [bitcoin](<https://devfeed.tech/tags/bitcoin.md>), [blockchain](<https://devfeed.tech/tags/blockchain.md>), [building](<https://devfeed.tech/tags/building.md>), [industry](<https://devfeed.tech/tags/industry.md>), [innovation](<https://devfeed.tech/tags/innovation.md>), [interest](<https://devfeed.tech/tags/interest.md>), [organizational](<https://devfeed.tech/tags/organizational.md>), [white-paper](<https://devfeed.tech/tags/white-paper.md>)

### AI overview

Ethereum's two-year anniversary prompts a retrospective on its public announcement, the early blockchain ecosystem, and the motivation to move from ideas in a white paper toward building a blockchain-driven system.

### Source excerpt

Last month marked the 2 year anniversary of Ethereum's public announcement at The North American Bitcoin Conference in Miami, Florida, USA. Amid much rumour and excitement, a sizeable crowd mobbed the young Vitalik Buterin after his on-stage announcement, questioning the merit and his desire to build such a system. ...