Dev tools · alternatives · 2026
24 alternatives to Reducing the size of PCSA to that of HyperLogLog
Contribute to seiflotfy/pcsa development by creating an account on GitHub.
This project presents a method to compress PCSA (probabilistic cardinality estimation algorithm) data structures to match the memory footprint of HyperLogLog while maintaining similar accuracy. Aimed at developers… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Reducing the size of PCSA to that of HyperLogLog launched in 2018; newer entries below may have overtaken it.
- 1
HyperLogLog with lots of sugar (Sparse, LogLog-Beta bias correction and TailCut space reduction) brought to you by Axiom - axiomhq/hyperloglog
2017 · github.com · its alternatives →
- 2
Zig library for HyperLogLog estimation. Contribute to axiomhq/zig-hyperloglog development by creating an account on GitHub.
2023 · github.com · its alternatives →
- 3
Here's a project I've been working on for the last few months. It's a new (I think) algorithm, that allows to adjust smoothly - and in real time - how many calculations you'd like to do during inference of an LLM model. It seems that it's possible to do just 20-25% of weight multiplications instead of all of them, and still get good inference results. I implemented it to run on M1/M2/M3 GPU. The mmul approximation itself can be pushed to run 2x fast before the quality of output collapses. The inference speed is just a bit faster than Llama.cpp's, because the rest of implementation…
2024 · asciinema.org · its alternatives →
- 4
Heap based scheme machine. GitHub Gist: instantly share code, notes, and snippets.
2025 · gist.github.com · its alternatives →
- 5
Hi HN! I'm just sharing a project I've been working on during the LLM Efficiency Challenge - you can now finetune Llama with QLoRA 5x faster than Huggingface's original implementation on your own local GPU. Some highlights: 1. Manual autograd engine - hand derived backprop steps. 2. QLoRA / LoRA 80% faster, 50% less memory. 3. All kernels written in OpenAI's Triton language. 4. 0% loss in accuracy - no approximation methods - all exact. 5. No change of hardware necessary. Supports NVIDIA GPUs since 2018+. CUDA 7.5+. 6. Flash Attention support via Xformers. 7. Supports 4bit and 16bit…
2023 · github.com · its alternatives →
- 6OA
I built an experiment that uses an overfitted transformer and arithmetic coding to compress individual files. Instead of training the model to generalize, I train a 900KB transformer to memorize a single file and predict the next byte. Those predictions are fed into an arithmetic coder to produce the compressed output. On a 100MB NYC taxi CSV, it compresses to about 7MB (~0.5 bits/byte). On a 100MB slice of enwik9, it compresses to about 21MB (~1.68 bits/byte). It's pretty slow right now (roughly 20–30 minutes of training and 45 minutes each for compression and decompression on my…
Jun 2026 · its alternatives →
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Vectorized executor to speed up PostgreSQL. Contribute to citusdata/postgres_vectorization_test development by creating an account on GitHub.
2014 · github.com · its alternatives →
- 8
Ollama for classical ML models. AOT compiler that turns XGBoost, LightGBM, scikit-learn, CatBoost & ONNX models into native C99 inference code. One command to load, one command to serve. 336x faster than Python inference. - kossisoroyce/timber
Mar 2026 · github.com · its alternatives →
- 9
HyperMinHash: Bringing intersections to HyperLogLog - axiomhq/hyperminhash
2018 · github.com · its alternatives →
- 10
Advanced Bloom Filter Based Algorithms for Efficient Approximate Data De-Duplication in Streams - jparkie/PDD
2016 · github.com · its alternatives →
- 11
A simple re-implementation of Google's sparsehash as a learning excercise. - qpfiffer/Simple-Sparsehash
2015 · github.com · its alternatives →
- 12
Probabilistic data structures for processing continuous, unbounded streams. - tylertreat/BoomFilters
2015 · github.com · its alternatives →
- 13AG
This is a vector index I built that supports insertion and k-nearest neighbors (k-NN) querying, optimized for GPUs. It operates entirely in CUDA and can process queries on half a billion vectors in under 200 milliseconds. The codebase is structured as a standalone library with an HTTP API for remote access. It’s intended for high-performance search tasks—think similarity search, AI model retrieval, or reinforcement learning replay buffers. The codebase is located at https://github.com/rodlaf/BinaryGPUIndex.
2025 · rlafuente.com · its alternatives →
- 14
LogLog based Cardinality Estimator. Contribute to seiflotfy/loglogbeta development by creating an account on GitHub.
2017 · github.com · its alternatives →
- 15
Minimal, readable LLM post-training experiments on one 8GB GPU. Measures forgetting, seed variance, and RL emergence. - pochenai/nano-llm-posttraining
Aug 2026 · github.com · its alternatives →
- 16
A look at modern database approaches and how Citus scales PG
2016 · softwareengineeringdaily.com · its alternatives →
- 17
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A probabilistic data structure service and storage - skizzehq/skizze
2016 · github.com · its alternatives →
- 19
Haskell re-implementation of STOKE, the stochastic superoptimizer - blaze/notebooks/tutorial.ipynb at master · bollu/blaze
2019 · github.com · its alternatives →
- 20WD
2023 · lama.nbnl.uk · its alternatives →
- 21
It's our new text-to-image model: a 9.3B single-stream diffusion transformer trained entirely from scratch. We focused heavily on controllability through structured JSON prompts, with strong text rendering, spatial awareness through bounding box guidance, and color palette control. It has the best text rendering of any open-weight model we've tested so far, and the NF4 quantized checkpoint runs on a single 24GB GPU. For more technical details and examples see our blog post: https://ideogram.ai/blog/ideogram-4.0/ We will be happy to answer any questions :)
Jun 2026 · github.com · its alternatives →
- 22
I wanted to know how fast a 26B mixture-of-experts model could run on a desktop CPU with no GPU. Got ~40 tok/s single-stream (lossless) and ~124 batched. The surprising part was the byte budget: for this model you compress the output head (32% of per-token bytes), not the experts (16%). The writeup has the bandwidth roofline and the dead-ends; the repo has the reproducible recipe. Happy to answer questions. Repo: https://github.com/arun-prasath2005/gemma4-cpu-moe
Jun 2026 · apeg.dev · its alternatives →
- 23
TLDR: A small, vendor-agnostic inference loop that turns token logprobs/perplexity/entropy into an extra pass and reasoning for LLMs. - Captures logprobs/top-k during generation, computes perplexity and token-level entropy. - Triggers at most one refine when simple thresholds fire; passes a compact “uncertainty report” (uncertain tokens + top-k alts + local context) back to the model. - In our tests on technical Q&A / math / code, a small model recovered much of “reasoning” quality at ~⅓ the cost while refining ~⅓ of outputs. I kept seeing “reasoning” models behave…
2025 · github.com · its alternatives →
- 24KC
If you’ve ever been curious about how GPT actually works under the hood, I built a small project you might find interesting. I implemented a GPT-style transformer from scratch in a single notebook—covering tokenization, embeddings, causal self-attention, training, and autoregressive text generation without relying on high-level abstractions. The focus was on mechanistic clarity rather than scale or performance, and the notebook is structured to read more like a technical walkthrough than an experiment log. Feedback from people who’ve built or studied transformers would be very welcome.
May 2026 · pythongiant.github.io · its alternatives →
Also compare
- An improved version of HyperLogLog alternatives
- HyperLogLog in Zig alternatives
- Speeding up LLM inference 2x times (possibly) alternatives
- Kent Dybvig's Scheme Machine in 400 Lines of C (Heap-Memory Model) alternatives
- 80% faster, 50% less memory, 0% loss of accuracy Llama finetuning alternatives
- Overfitted a 900KB Transformer to Compress a 100MB CSV into 7MB alternatives
Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →