# Numba

Published articles for Numba.

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

## CUDA Python 1.0: Stable APIs, One Foundation, Full Platform Access

DevFeed: [CUDA Python 1.0: Stable APIs, One Foundation, Full Platform Access](<https://devfeed.tech/articles/cuda-python-1-0-stable-apis-one-foundation-full-platform-access-6786.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/cuda-python-1-0-stable-apis-one-foundation-full-platform-access/>)

Author: Elizabeth Goodman

Published: 2026-08-25T15:00:00Z

Content type: article

Language: en

Sources: [NVIDIA Developer](<https://devfeed.tech/sources/nvidia-developer.md>), [NVIDIA Technical Blog](<https://devfeed.tech/sources/nvidia-technical-blog.md>)

Topics: [CUDA](<https://devfeed.tech/topics/cuda.md>), [Python](<https://devfeed.tech/topics/python.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [C++](<https://devfeed.tech/topics/c-plus-plus.md>), [toolchain](<https://devfeed.tech/topics/toolchain.md>), [PyTorch](<https://devfeed.tech/topics/pytorch.md>), [RAPIDS](<https://devfeed.tech/topics/rapids.md>), [releases](<https://devfeed.tech/topics/releases.md>)

Tags: [c-plus-plus](<https://devfeed.tech/tags/c-plus-plus.md>), [cuda](<https://devfeed.tech/tags/cuda.md>), [data-science](<https://devfeed.tech/tags/data-science.md>), [developer-tools-techniques](<https://devfeed.tech/tags/developer-tools-techniques.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [numba](<https://devfeed.tech/tags/numba.md>), [python](<https://devfeed.tech/tags/python.md>), [pytorch](<https://devfeed.tech/tags/pytorch.md>), [rapids](<https://devfeed.tech/tags/rapids.md>), [release](<https://devfeed.tech/tags/release.md>), [toolchain](<https://devfeed.tech/tags/toolchain.md>)

### AI overview

CUDA Python 1.0 makes the CUDA platform accessible from Python through stable, versioned components, including runtime access, low-level CUDA C API bindings, parallel algorithms, component discovery, and NVIDIA math libraries. The release establishes a shared foundation for Python GPU libraries and introduces semantic-versioning commitments for public APIs.

### Source excerpt

For years, a Python developer who needed a GPU had two realistic choices: Learn NVIDIA CUDA C++ well enough to write an extension, set up a build toolchain, and...

## Searching for RH Counterexamples -- Unbounded Integers

DevFeed: [Searching for RH Counterexamples -- Unbounded Integers](<https://devfeed.tech/articles/searching-for-rh-counterexamples-unbounded-integers-40440.md>)

Original publisher: [Read original article](<https://www.jeremykun.com/2020/10/13/searching-for-rh-counterexamples-unbounded-integers/>)

Published: 2020-10-13T09:00:00Z

Content type: article

Language: en

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

Topics: [Database](<https://devfeed.tech/topics/database.md>), [Python](<https://devfeed.tech/topics/python.md>), [Software Engineering](<https://devfeed.tech/topics/software-engineering.md>), [Numba](<https://devfeed.tech/topics/numba.md>), [Sorting](<https://devfeed.tech/topics/sorting.md>)

Tags: [arbitrary-precision-arithmetic](<https://devfeed.tech/tags/arbitrary-precision-arithmetic.md>), [database](<https://devfeed.tech/tags/database.md>), [databases](<https://devfeed.tech/tags/databases.md>), [mathematics](<https://devfeed.tech/tags/mathematics.md>), [numba](<https://devfeed.tech/tags/numba.md>), [number-theory](<https://devfeed.tech/tags/number-theory.md>), [open-closed](<https://devfeed.tech/tags/open-closed.md>), [postgres](<https://devfeed.tech/tags/postgres.md>), [python](<https://devfeed.tech/tags/python.md>), [riemann-hypothesis](<https://devfeed.tech/tags/riemann-hypothesis.md>), [software](<https://devfeed.tech/tags/software.md>), [software-engineering](<https://devfeed.tech/tags/software-engineering.md>), [sorting](<https://devfeed.tech/tags/sorting.md>), [superabundant-numbers](<https://devfeed.tech/tags/superabundant-numbers.md>)

### AI overview

This article examines how searching for Riemann Hypothesis counterexamples reaches the limits of 64-bit integers. It explains unbounded integer arithmetic and considers database and performance alternatives for storing and processing the search results.

### Source excerpt

We're ironically searching for counterexamples to the Riemann Hypothesis. Setting up Pytest Adding a Database Search strategies In the last article, we improved our naive search from "try all positive integers" to enumerate a subset of integers (superabundant numbers), which RH counterexamples are guaranteed to be among. These numbers grow large, fast, and we quickly reached the limit of what 64 bit integers can store. Unbounded integer arithmetic is possible on computers, but it requires a special software implementation.