--- title: Streamlining CUB with a Single-Call API | daily.dev description: CUDA 13.1 introduces a new single-call API for CUB (CUDA Core Compute Libraries) that simplifies GPU primitive algorithm usage by eliminating the traditional... canonical: https://daily.dev/posts/streamlining-cub-with-a-single-call-api-p4equ0mqw twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Streamlining CUB with a Single-Call API | daily.dev og:description: CUDA 13.1 introduces a new single-call API for CUB (CUDA Core Compute Libraries) that simplifies GPU primitive algorithm usage by eliminating the traditional... og:url: https://daily.dev/posts/streamlining-cub-with-a-single-call-api-p4equ0mqw og:image: https://api.daily.dev/og/posts/p4Equ0mQW.png og:image:alt: Streamlining CUB with a Single-Call API og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Streamlining CUB with a Single-Call API **[NVIDIA Developer](https://daily.dev/sources/nvidiadev)** · 8 min read · 0 upvotes · 0 comments ## Summary CUDA 13.1 introduces a new single-call API for CUB (CUDA Core Compute Libraries) that simplifies GPU primitive algorithm usage by eliminating the traditional two-phase pattern of memory estimation and allocation. The new API manages memory allocation automatically under the hood with zero performance overhead, while introducing an extensible environment argument that allows developers to configure execution options like custom memory resources and streams. This change addresses the widespread practice of wrapping CUB calls with macros (as seen in PyTorch) and provides a cleaner, more maintainable interface without sacrificing the flexibility needed for advanced use cases. ## Full article daily.dev links to this article rather than hosting it. 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