# A System Perspective

Published articles for A System Perspective.

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## Physics-Based Validation: The Foundation Of Trustworthy Agentic EDA

DevFeed: [Physics-Based Validation: The Foundation Of Trustworthy Agentic EDA](<https://devfeed.tech/articles/physics-based-validation-the-foundation-of-trustworthy-agentic-eda-106363.md>)

Original publisher: [Read original article](<https://semiengineering.com/physics-based-validation-the-foundation-of-trustworthy-agentic-eda/>)

Author: Emma-Jane Crozier

Published: 2026-10-29T07:07:05Z

Content type: article

Language: en

Sources: [Semiconductor Engineering](<https://devfeed.tech/sources/semiconductor-engineering.md>)

Topics: [Chip design](<https://devfeed.tech/topics/chip-design.md>), [Loop Engineering](<https://devfeed.tech/topics/loop-engineering.md>), [agentic-coding](<https://devfeed.tech/topics/agentic-coding.md>)

Tags: [3d-ic](<https://devfeed.tech/tags/3d-ic.md>), [3d-ics](<https://devfeed.tech/tags/3d-ics.md>), [a-system-perspective](<https://devfeed.tech/tags/a-system-perspective.md>), [agentic](<https://devfeed.tech/tags/agentic.md>), [agentic-ai](<https://devfeed.tech/tags/agentic-ai.md>), [agentic-coding](<https://devfeed.tech/tags/agentic-coding.md>), [agentic-engineering](<https://devfeed.tech/tags/agentic-engineering.md>), [agentic-workflow](<https://devfeed.tech/tags/agentic-workflow.md>), [agents](<https://devfeed.tech/tags/agents.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-agent](<https://devfeed.tech/tags/ai-agent.md>), [ai-factories](<https://devfeed.tech/tags/ai-factories.md>), [analysis](<https://devfeed.tech/tags/analysis.md>), [arbiter](<https://devfeed.tech/tags/arbiter.md>), [architecture](<https://devfeed.tech/tags/architecture.md>), [blogs-sld](<https://devfeed.tech/tags/blogs-sld.md>), [eda](<https://devfeed.tech/tags/eda.md>), [engineering](<https://devfeed.tech/tags/engineering.md>), [engines](<https://devfeed.tech/tags/engines.md>), [multiphysics](<https://devfeed.tech/tags/multiphysics.md>), [physics](<https://devfeed.tech/tags/physics.md>), [physics-based-design](<https://devfeed.tech/tags/physics-based-design.md>), [semiconductor](<https://devfeed.tech/tags/semiconductor.md>), [semiconductor-engineering](<https://devfeed.tech/tags/semiconductor-engineering.md>), [siemens-eda](<https://devfeed.tech/tags/siemens-eda.md>), [system-level-design](<https://devfeed.tech/tags/system-level-design.md>), [validation](<https://devfeed.tech/tags/validation.md>), [verification](<https://devfeed.tech/tags/verification.md>)

### AI overview

The article's central claim is that trustworthy agentic EDA requires deterministic, physics-based EDA engines to validate each agent decision before the workflow proceeds. If a result misses physical constraints, the agent identifies and resolves the issue; continuous checks are intended to prevent errors from compounding in long autonomous runs. The 3D-IC example uses Fuse EDA AI Agent with MCP servers and skill files to connect Siemens tools, while Claude Code orchestrates a nine-stage workflow across seven tools for more than 12 hours. Each stage uses signoff-grade solvers, covering tasks such as floor planning, power analysis, thermal simulation, parasitic extraction, and SPICE simulation. The article reports sweeps of 200-500+ design points and claims faster tool configuration and reduced engineering effort; these are presented as outcomes of the example, not independently substantiated in the excerpt.

### Source excerpt

What self-verifying agents validate their decisions against and why physics-based engines are the authority on correctness. The post Physics-Based Validation: The Foundation Of Trustworthy Agentic EDA appeared first on Semiconductor Engineering.

## Why Temperature 0 Isn't Deterministic in LLM Inference

DevFeed: [Why Temperature 0 Isn't Deterministic in LLM Inference](<https://devfeed.tech/articles/why-temperature-0-isn-t-deterministic-in-llm-inference-102564.md>)

Original publisher: [Read original article](<https://blog.dailydoseofds.com/p/why-temperature-0-isnt-deterministic>)

Author: Avi Chawla

Published: 2026-10-26T23:12:43Z

Content type: article

Language: en

Sources: [Daily Dose of Data Science](<https://devfeed.tech/sources/daily-dose-of-data-science.md>)

Topics: [LLM optimization](<https://devfeed.tech/topics/llm-optimization.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [Temperature settings in AI](<https://devfeed.tech/topics/temperature-settings-in-ai.md>), [vllm](<https://devfeed.tech/topics/vllm.md>), [LLM observability](<https://devfeed.tech/topics/llm-observability.md>)

Tags: [000](<https://devfeed.tech/tags/000.md>), [2](<https://devfeed.tech/tags/2.md>), [3](<https://devfeed.tech/tags/3.md>), [a-system-perspective](<https://devfeed.tech/tags/a-system-perspective.md>), [about](<https://devfeed.tech/tags/about.md>), [addition](<https://devfeed.tech/tags/addition.md>), [agent](<https://devfeed.tech/tags/agent.md>), [agentic](<https://devfeed.tech/tags/agentic.md>), [alignment](<https://devfeed.tech/tags/alignment.md>), [all](<https://devfeed.tech/tags/all.md>), [also](<https://devfeed.tech/tags/also.md>), [api](<https://devfeed.tech/tags/api.md>), [inference](<https://devfeed.tech/tags/inference.md>), [interview](<https://devfeed.tech/tags/interview.md>), [isn-t](<https://devfeed.tech/tags/isn-t.md>), [llm](<https://devfeed.tech/tags/llm.md>), [llm-inference](<https://devfeed.tech/tags/llm-inference.md>), [popular](<https://devfeed.tech/tags/popular.md>), [question](<https://devfeed.tech/tags/question.md>), [temperature](<https://devfeed.tech/tags/temperature.md>)

### AI overview

Temperature 0 removes sampling but does not guarantee identical LLM outputs: batch size can change floating-point addition order in GPU kernels, slightly shifting logits and flipping near-tied token choices. Because generation is autoregressive, one token flip can lead to widely different completions. The excerpt reports 80 completions across 1,000 Qwen3-235B runs; batch-invariant kernels made all 1,000 identical, at a speed cost. Reported Qwen3-8B timings were 26 seconds for default vLLM, 55 for its first deterministic version, and 42 after an attention-kernel improvement. It notes beta support via `VLLM_BATCH_INVARIANT=1` and an SGLang deterministic-inference flag with a reported 34.35% average slowdown. Reproducibility matters especially for evals, production debugging, and on-policy RL.

### Source excerpt

...explained visually (a popular LLM interview question).

## Managing 3D-IC Design And IP

DevFeed: [Managing 3D-IC Design And IP](<https://devfeed.tech/articles/managing-3d-ic-design-and-ip-59319.md>)

Original publisher: [Read original article](<https://semiengineering.com/managing-3d-ic-design-and-ip/>)

Author: Keith Felton

Published: 2026-09-24T07:05:05Z

Content type: article

Language: en

Sources: [Semiconductor Engineering](<https://devfeed.tech/sources/semiconductor-engineering.md>)

Topics: [3D](<https://devfeed.tech/topics/3d.md>), [Data Management](<https://devfeed.tech/topics/data-management.md>), [data-architecture](<https://devfeed.tech/topics/data-architecture.md>), [version](<https://devfeed.tech/topics/version.md>), [Software](<https://devfeed.tech/topics/software.md>), [Specifications](<https://devfeed.tech/topics/specifications.md>)

Tags: [3d](<https://devfeed.tech/tags/3d.md>), [3d-ics](<https://devfeed.tech/tags/3d-ics.md>), [a-system-perspective](<https://devfeed.tech/tags/a-system-perspective.md>), [blogs-sld](<https://devfeed.tech/tags/blogs-sld.md>), [chiplets](<https://devfeed.tech/tags/chiplets.md>), [components](<https://devfeed.tech/tags/components.md>), [data](<https://devfeed.tech/tags/data.md>), [data-management](<https://devfeed.tech/tags/data-management.md>), [defects](<https://devfeed.tech/tags/defects.md>), [design](<https://devfeed.tech/tags/design.md>), [engineering](<https://devfeed.tech/tags/engineering.md>), [heterogeneous-integration](<https://devfeed.tech/tags/heterogeneous-integration.md>), [integration](<https://devfeed.tech/tags/integration.md>), [ip](<https://devfeed.tech/tags/ip.md>), [revision-control](<https://devfeed.tech/tags/revision-control.md>), [semiconductor](<https://devfeed.tech/tags/semiconductor.md>), [siemens-eda](<https://devfeed.tech/tags/siemens-eda.md>), [software](<https://devfeed.tech/tags/software.md>), [system-level-design](<https://devfeed.tech/tags/system-level-design.md>), [traceability](<https://devfeed.tech/tags/traceability.md>)

### AI overview

This article explains how design data management, traceability, IP management, and revision control support multi-chiplet 3D-IC heterogeneous integration. It describes the risks of fragmented design data, including defects, delays, and product failure, and discusses a centralized, access-controlled approach to managing design IP through tape-out.

### Source excerpt

Design data management, traceability, and revision control are critical for multi-chiplet heterogeneous integration. The post Managing 3D-IC Design And IP appeared first on Semiconductor Engineering.