Performance
16 articles on Performance 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.
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.
Preventing Missed Matches in Parallel Web Worker Text Search
Parallel text search silently misses matches at the boundary between chunks. We fixed it, used in every Newcastle document-processing engagement we ship.
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.
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.
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.
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.
Zero-Copy Parallel Processing with SharedArrayBuffer in JavaScript
Zero-copy parallel AI compute in a browser, using every CPU core. How Newcastle SMBs get server-grade performance on standard laptops.
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.
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.
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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