A primer on Roaring bitmaps: what they are and how they work
A detailed primer on Roaring bitmaps explaining what they are, how they're different from traditional bitmaps, and how they work internally.
Better bitmap performance with Roaring bitmaps
Bitmap indexes are commonly used in databases and search engines. By exploiting bit-level parallelism, they can significantly accelerate queries. However, they can use much memory, and thus we might prefer compressed bitmap indexes. Following Oracle's lead, bitmaps are often compressed using run-length encoding (RLE). Building on prior work, we introduce the Roaring compressed bitmap format: it uses packed arrays for compression instead of RLE. We compare it to two high-performance RLE-based bitmap encoding techniques: WAH (Word Aligned Hybrid compression scheme) and Concise (Compressed `n' Composable Integer Set). On synthetic and real data, we find that Roaring bitmaps (1) often compress significantly better (e.g., 2 times) and (2) are faster than the compressed alternatives (up to 900 times faster for intersections). Our results challenge the view that RLE-based bitmap compression is best.
An entire Social Network in 1.6GB (GraphD Part 2)
Roaring Bitmaps offer an even more efficient way to store and query an entire social graph, fitting the entire network of 5.5M users and 164M+ follows into a ~1.6GB SQLite DB on disk.
TurboQuant: Redefining AI efficiency with extreme compression
Amir Zandieh, Research Scientist, and Vahab Mirrokni, VP and Google Fellow, Google Research
A 4-Bit Model and a 1-Bit Index
Running NVFP4 Nemotron on a CPU, then mapping every embedding-compression method at matched byte budgets. The two quantizations compose.
Squoosh
Squoosh is the ultimate image optimizer that allows you to compress and compare images with different codecs in your browser.
TinyPNG – Compress AVIF, WebP, PNG and JPEG images
Free online image optimizer for faster websites! Reduce the file size of your AVIF, WEBP, JPEG and PNG images while preserving the image quality.
Semantic Compression
An introduction to the idea that code should be approached with a mindset towards compressing it semantically, rather than orienting it around objects.
Dictionary Compression is finally here, and it's ridiculously good
Dictionary compression could completely change how applications send data over the web. It's recently gained broad support, and offers absurd real-world...
I built ChatGPT with Minecraft redstone!
PrismML — Introducing Bonsai 2 27B: Near-Lossless Compression in a 9x Smaller Footprint
Ternary Bonsai 2 27B retains 98.2% of Qwen3.8 27B benchmark performance in a 5.9GB footprint, with multimodal and agentic capabilities.
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1-bit Hokusai’s ”The Great Wave” – Hypertalking
5 years ago I started a now completely stalled project (fingers crossed I can figure out how to restart soon) to draw all of Hokusai’s 36 views of Mount Fuji as 1-bit pixel art.
Benchmarking Subquadratic’s latest model & SSA Kernel | Appen
56× faster than FlashAttention-2 at 1M tokens. Independent efficiency, retrieval, and SWE-Bench benchmark of sparse self-attention. Download the full report.
visualising data structures and algorithms through animation - VisuAlgo
VisuAlgo was conceptualised in 2011 by Associate Professor Steven Halim (NUS School of Computing) as a tool to help his students better understand data structures and algorithms, by allowing them to learn the basics on their own and at their own pace. Together with his students from the National University of Singapore, a series of visualizations were developed and consolidated, from simple sorting algorithms to complex graph data structures. Though specifically designed for the use of NUS students taking various data structure and algorithm classes (CS1010/equivalent, CS2040/equivalent (inclusive of IT5003)), CS3230, CS3233, and CS4234), as advocators of online learning, we hope that curious minds around the world will find these visualizations useful as well.
COLMAP Online · Feature Detection
A fully local browser workflow for COLMAP and Gaussian Splatting.
