Source group · 7 artworks · 1 families
anadol · webgpu
Refik Anadol studio lineage — WebGPU-flavored data sculptures and machine hallucinations.
Path on disk: library_external/anadol_webgpu/
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2D FFT Texture Spectrum (WebGPU butterfly FFT)
anadol_webgpu · fft2dTexture
The WebGPU butterfly 2D FFT pattern: stage by stage, a @compute shader reads two texels per output (input[p] and twiddle-weighted input[q]) and writes the combined result; after log2(N) horizontal stages, transpose, and log2(N) vertical stages, the 2D FFT is complete.
Compute Particle System (WebGPU @compute pattern)
anadol_webgpu · computeParticleSystem
The canonical WebGPU 'compute-to-render' pattern: a @compute shader updates N particles in a storage buffer (one thread per particle, simple Verlet-style integration: v += gravity; v *= drag; p += v; bounce off walls; life++; respawn if life>max), and a render pass consumes the same buffer as vertex data to draw point sprites.
Data Particle Field (Refik Anadol — Machine Hallucinations / AI Data Sculptures)
anadol_webgpu · dataParticleField
Inspired by Refik Anadol Studio's AI Data Sculptures and 'data universe' portraits (e.g.
Dreamscape Field (Refik Anadol — Dreams / Nature Dreams)
anadol_webgpu · dreamscapeField
Inspired by Refik Anadol Studio's Dreams series (Nature Dreams, Urban Dreams, Space Dreams and the MoMA Fluid Dreams algorithm): a smooth low-frequency Perlin noise field drives slow global drift while a finer detail octave adds turbulent perturbation — Anadol's fluid solver aesthetic realised with cheap numpy.
Latent Walk (Refik Anadol — Unsupervised / Machine Hallucinations)
anadol_webgpu · latentWalk
Inspired by Refik Anadol Studio's Unsupervised — Machine Hallucinations — MoMA (2022): a chain of N points is sampled from a synthetic 64-dimensional latent space (a smoothed random walk) and projected to 2D via a fixed random matrix; the path is integrated step-by-step with spherical-linear interpolation between adjacent chain points, so the rendered trail visualises the path the 'latent space browser' would take through the embedding.
Parallel Reduction (WebGPU workgroup-shared-memory tree reduction)
anadol_webgpu · parallelReduction
The classic WebGPU parallel-reduction pattern: load N values into workgroup-shared memory, workgroupBarrier(), tree-reduce by stride (shared[lid.x] = op(shared[lid.x], shared[lid.x + stride]); stride /= 2), workgroupBarrier(), and emit per-workgroup partials from thread 0.
Tile Blur (WebGPU separable Gaussian tile-shared-memory blur)
anadol_webgpu · tileBlur
The WebGPU separable Gaussian blur primitive: a workgroup of TILE×TILE threads loads a tile+halo of the source image into workgroup-shared memory, workgroupBarrier(), convolves each pixel with a 1D Gaussian along the row, writes to a ping-pong texture; then a second compute pass applies the column-direction Gaussian on the intermediate texture.