Hacker NewsI designed a nibble-oriented CPU in Verilog to build a scientific calculator
https://github.com/gdevic/FPGA-Calculator
#HackerNews #nibbleCPU #Verilog #FPGA #calculator #scientificcomputing #hardwaredesign
Peter — SSIStandard‑Slope Integration (SSI) — Link to Post #7: Why SSI is general-purpose
A new, first-of-its-kind class of derivative-driven integration operators built solely from slope information.
SSI is real, not a trick — it’s a general-purpose integration operator built from first principles.
Link: https://mathstodon.xyz/@BlueNovaX/116516955308646107
#numericalanalysis #scientificcomputing #mathematics #integration #StandardSlopeIntegration #SSI
Peter — SSI (@[email protected])
Standard‑Slope Integration (SSI) — Post #7: Why SSI is general-purpose A new, first-of-its-kind class of derivative-driven integration operators built solely from slope information. Although SSI excels in difficult cases, it isn’t designed only for failures. Its derivative-driven structure and invariant-preserving iteration make it broadly applicable across smooth, irregular, and mixed-structure integrands. The same reconstruction principles that stabilize challenging cases also perform reliably in ordinary cases, giving SSI a uniquely wide operational range without unnecessary adjustments. This general-purpose behavior follows directly from SSI’s underlying structure and nothing else. #numericalanalysis #scientificcomputing #mathematics #integration #StandardSlopeIntegration #SSI
Virgile AndreaniOh so the new garbage collector (GC) introduced in Python 3.14.0 was indeed memory hungry! That could explain why a pytest run that was working fine on 3.13 went OOM as soon as I switched it to 3.14. I am glad there is an explanation!
From what I understand the old GC was swapped back on for 3.14.5 and later.
sayzardTibo (@thsottiaux)
OpenAI가 과학자들을 위한 Codex의 활용이 수학, 물리, 화학, 생물학 등 다양한 분야에서 강한 반응을 얻고 있으며, 현재 기능 개선을 진행 중이라고 밝혔다. 연구·과학 작업에 더 유용한 AI 코딩/에이전트 도구로 발전할 가능성을 보여주는 업데이트다.
Start here: Standard-Slope Integration (SSI)
A new, first-of-its-kind class of derivative-driven integration operators built solely from slope information.
If you’re new to my work, this post links to the full SSI series—a structured overview of a first-of-its-kind, derivative-driven integration operator built on structural iteration invariants and slope-based reconstruction. The recap summarizes all seven posts in order and provides the conceptual foundation for understanding SSI.
Series recap:
https://mathstodon.xyz/@BlueNovaX/116523359117197532
Repository with details and examples:
https://github.com/BlueNovaX/standard-slope-integration
#numericalanalysis #scientificcomputing #mathematics #integration #StandardSlopeIntegration #SSI
Peter — SSI (@[email protected])
Standard‑Slope Integration (SSI): Series recap A new, first-of-its-kind class of derivative-driven integration operators built solely from slope information. Over the past several posts, I’ve outlined the core ideas behind Standard-Slope Integration (SSI): 1. Why derivative-driven structure matters 2. How structural iteration invariants stabilize reconstruction 3. Why SSI remains robust in cases of instability or failure 4. How slope-based reconstruction differs from area accumulation 5. How SSI diverges from classical quadrature 6. A simple example of SSI behavior 7. Why the method is genuinely general-purpose Together, these posts sketch the conceptual foundation of SSI and why it represents a new class of integration operators. More details and examples are available in the repository: https://github.com/BlueNovaX/standard-slope-integration #numericalanalysis #scientificcomputing #mathematics #integration #StandardSlopeIntegration #SSI
Standard‑Slope Integration (SSI) — Post #7: Why SSI is general-purpose
A new, first-of-its-kind class of derivative-driven integration operators built solely from slope information.
Although SSI excels in difficult cases, it isn’t designed only for failures. Its derivative-driven structure and invariant-preserving iteration make it broadly applicable across smooth, irregular, and mixed-structure integrands. The same reconstruction principles that stabilize challenging cases also perform reliably in ordinary cases, giving SSI a uniquely wide operational range without unnecessary adjustments.
This general-purpose behavior follows directly from SSI’s underlying structure and nothing else.
#numericalanalysis #scientificcomputing #mathematics #integration #StandardSlopeIntegration #SSI
AmartyaMy implementation of the GaussSeidel smoother using a Diagnol direct access scheme in OpenFOAM as compared to the default GS smoother LDU gives almost ~50% improvements in cache misses and hits for a structured 3D cavity tutorial. Profiled using the amazing LIKWID profiler. Will share a deep technical report soon. Check it out and use - https://github.com/amartyadav/DIAGaussSeidel-Smoother-OpenFOAM
#hpc #scientificcomputing #computationalphysics #cfd #openfoam #likwid #softwaredevelopment #cpp
#hpc #scientificcomputing #computationalphysics #cfd #openfoam #likwid #softwaredevelopment #cpp
Been working on my Linux machine for 3 months now at work - comp. physics, hpc, etc.
Tried working on my MBP yesterday (after around 5 months of not using it for development) - while a superior machine h/w wise, I really couldn't stand macOS.
Linux just works - better even.
#linux #macos #development #hpc #scientificcomputing #computationalphysics #ux #ubuntu #SoftwareDevelopment
Bloodhound code sniffs out copied-and-pasted numerical data – Retraction Watch
https://retractionwatch.com/2026/04/06/data-duplications-errors-open-repositories-markus-englund/
#ResearchIntegrity #OpenData #ScientificComputing #DataEthics #AcademicMastodon
Project JupyterMyST Markdown 1.8 introduces updates that improve how structured, machine-readable content is created and managed across Jupyter workflows.
These changes support better interoperability, extensibility and validation for computational documents, making it easier to build reusable publishing pipelines.
Learn more: https://blog.jupyter.org/whats-new-in-myst-markdown-1-8-2-b7ae8975b03e
