WebGPU
28 articles on WebGPU from Ayoob AI, the full code AI automation agency based in Newcastle upon Tyne.
Arithmetic Intensity Explained: The Formula and Why It Predicts GPU Speedup
Arithmetic intensity is the ratio of compute operations to memory bytes moved. The formula, worked GEMM examples, and why it decides if GPU or CPU wins.
WebGPU for Enterprise: A Complete Guide to Browser GPU Computing
WebGPU puts GPU-class compute inside the browser, on hardware you own. The complete guide for enterprise: private on-device processing, no cloud GPU bills.
The Ayoob AI Architecture: Merging CPU, Workers, and WebGPU
Architectural overview of our heterogeneous dispatch engine: workload characterization and precision analysis route work to CPU, Web Workers, or WebGPU.
Trust but Verify: Validating GPU Float32 Math on the CPU
A post-dispatch spot-check re-computes 16 GPU Float32 outputs in Float64 on the CPU. If relative error exceeds tolerance, it discards and re-runs on CPU.
Why Hardcoded GPU Dispatch Thresholds Fail in the Browser
Hardcoded GPU thresholds break across devices. Self-calibrating dispatch makes AI software fast on every laptop, engineered for UK SMB workloads.
WebGPU Memory Limits: maxStorageBufferBindingSize
maxStorageBufferBindingSize runs from 128 MB on mobile to 4 GB on desktop. How to query it at runtime, route oversized datasets to CPU, and pool buffers.
Predicting GPU Hash Map Collisions with the Chao1 Estimator
GPU databases crash when GROUP BY cardinality is guessed wrong. The Chao1 estimator predicts it, used in our Newcastle-built analytics engine.
Executing SQL WHERE Clauses on the GPU with Dictionary Encoding
Filtering 10M customer records on a GPU in a browser, under 200ms. The technique powering our Newcastle AI data-query engines.
The Variable-Width Problem: Why UTF-8 Breaks WebGPU Text Search
GPUs break on variable-width text (apostrophes, emojis, names). Our UTF-8-safe engine is why Newcastle law and finance firms trust our AI search.
Bypassing Array.prototype.sort() with IEEE 754 Bit-Transforms
V8's TimSort coerces numbers to strings. Transform IEEE 754 floats to order-preserving unsigned ints for radix-256 CPU sort and GPU bitonic-merge sort.
The First Non-Comparison Float Sort in JavaScript
Array.prototype.sort() is broken for numbers. We built a three-tier adaptive engine dispatching between CPU, Web Workers, and WebGPU shaders. Here is how.
Building Fault-Tolerant AI Workflows: Handling WebGPU Device Loss
Browser GPUs crash without warning. Our cascading fallback watches GPUDevice.lost, invalidates cached state, and re-dispatches to CPU workers instantly.
WebGPU Atomic Contention: When to Stop Using the GPU
Sometimes the GPU is slower than the CPU. Knowing when is the real engineering, the decision logic behind our Newcastle AI builds.
Why On-Device WebGPU Costs Less Than Cloud LLM APIs
Routing every sort, filter, and aggregation to a cloud server costs $0.12 to $0.85 per 1,000 queries. On-device WebGPU dispatch removes that compute cost.
Preventing Silent Numerical Degradation in GPU-Accelerated Finance AI
GPU-accelerated finance AI silently loses precision below the pound. Our Float32 safety guard catches it before it hits your ledger, engineered in Newcastle.
Eliminating PCIe Bus Bottlenecks in Enterprise AI Compliance Tools
Most compliance AI wastes 80% of its time shuffling data between CPU and GPU. We eliminated that. Built for UK regulated industries.
Real-Time Threat Detection with GPU-Accelerated Streaming Corpora
Live log streams grow nonstop. Searched-frontier tracking extends the corpus and dispatches the GPU only against unsearched data for real-time detection.
GPU Pattern Matching for Gaming Anti-Cheat at Scale
Standard regex cannot run on GPUs. Our two-phase engine uses character-frequency histograms to cut 97% of candidates before byte-level fraud matching.
Sub-200ms Hospitality CRMs: Moving SQL Relational Operators to WebGPU
Server-side CRM queries add 150 to 400 ms each. Our Adaptive WebGPU Data Query Engine runs relational operators on in-memory columnar data at the client.
Mitigating Atomic Contention in Parallel Browser Environments
When thousands of GPU threads compete for one atomic address, throughput collapses. Our engine profiles density and routes to CPU before the GPU stalls.
The Hidden Compute Costs of Array.prototype.sort() in Enterprise SaaS
V8's TimSort runs 20 million comparator callbacks per million elements, each crossing the native-to-JS boundary. Our adaptive GPU sort bypasses this.
Engineering Resilient Compute Pipelines: Handling WebGPU Device Loss
Browser GPUs crash without warning. Our engine detects device loss via the GPUDevice.lost promise and transparently re-dispatches to CPU mid-operation.
Why Reduced-Precision GPU Arithmetic is Dangerous for Enterprise Finance
WebGPU forces Float64 financial data into Float32, silently corrupting values above 16,777,216. How a precision guard blocks risky GPU dispatch.
The Two-Phase GPU Text Search Algorithm for Massive Log Files
Brute-force matching on 1 million log entries takes 800 ms on CPU. Our two-phase GPU algorithm uses a histogram pre-filter to cut up to 97% of candidates.
IEEE 754 Bit-Transforms for High-Speed Float Processing in JavaScript
JavaScript uses Float64, WebGPU needs Float32. The IEEE 754 bit-transform converts floats to sort-order-preserving integers, with a Float32 safety guard.
GPU-Accelerated Relational Queries: Moving the Database to the Browser
GPU-accelerated relational queries in the browser. Our WebGPU Data Query Engine routes each operator to CPU, Web Workers, or GPU to cut dashboard latency.
Handling SIMD Branch Divergence in Browser-Based Compute Shaders
GPU wavefronts serialize when threads diverge. We detect divergence-prone WebGPU workloads at dispatch time and route them to the CPU tier instead.
Why WebGPU is Replacing Web Workers for Enterprise Data Processing
When to replace Web Workers with WebGPU for enterprise data processing. The calibration tells you which. Built by a Newcastle AI team.
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