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ParaWeb: Parallel Programming Patterns for Web Development — arXiv:2608.19935

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.19935
License (as archived): CC0-1.0
Archived: 2026-10-18T11:40:51.021Z
SHA-256 of the archived text: cf8481bad81cb10819dcdf3260c4fe481bef0f87eb376e0cb846b77236b1f4d0
Stable URL of this page: https://metraipolis.com/documento/dc_7e2669aaaebf

How to cite

ParaWeb: Parallel Programming Patterns for Web Development — arXiv:2608.19935 — arXiv (en), https://arxiv.org/abs/2608.19935 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_7e2669aaaebf (Metraipolis archive dc_7e2669aaaebf, sha256 cf8481bad81cb10819dcdf3260c4fe481bef0f87eb376e0cb846b77236b1f4d0)

BibTeX

@misc{dc7e2669aaaebf,
  title = {ParaWeb: Parallel Programming Patterns for Web Development — arXiv:2608.19935},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.19935},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_7e2669aaaebf; sha256 cf8481bad81cb10819dcdf3260c4fe481bef0f87eb376e0cb846b77236b1f4d0},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.19935. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Modern web applications increasingly require computationally intensive processing, yet JavaScript, the dominant language of the web, has traditionally been limited to a single-threaded execution model. this http URL Worker Threads and browser Web Workers provide low-level mechanisms for parallel execution, but developers lack high-level abstractions that capture recurring parallel structures as reusable patterns. In this paper, we present ParaWeb, a TypeScript library that implements ten parallel programming patterns for server-side this http URL , client-side browser environments, and WebGPU compute shaders. ParaWeb provides three implementation variants for each pattern: a message-passing (MP) variant based on structured cloning via postMessage, a shared-buffer (Shared) variant that uses SharedArrayBuffer with typed array views, and a GPU variant that uses WebGPU compute shaders for hardware-accelerated execution. We describe the architecture, design decisions, and pattern-specific implementation strategies, and we evaluate the performance of all thirty implementations across three data sizes. Experimental evaluation results show that the CPU-based variants achieve speedups of up to 11.6x with 16 threads for compute-bound patterns, while the GPU variants reach speedups of up to 260x for compute-bound patterns with high arithmetic intensity such as Farm, Scatter, Reduce, and Map. A case study on five image-convolution filters further shows that GPU acceleration reaches up to 414x speedup over single-threaded CPU on non-separable kernels, with consistent scaling across 1024x1024$, 2048x2048$, and 4K images.

Tema degli esploratori: calcolo e infrastrutture (retro-catalogo arXiv: annunci del 2026-08-21 in cs.DC).
Categorie arXiv: Distributed, Parallel, and Cluster Computing (cs.DC).
Pagina del lavoro: https://arxiv.org/abs/2608.19935 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-18T11:38:59.517Z dalla pagina https://arxiv.org/catchup/cs.DC/2026-08-21?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).