A 2.78-trillion-parameter Kimi K3 running inference on a single CPU in 8.24 GB of RAM. Portable C99: no BLAS, no framework, no GPU.
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Oct 2, 2026 - C
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A 2.78-trillion-parameter Kimi K3 running inference on a single CPU in 8.24 GB of RAM. Portable C99: no BLAS, no framework, no GPU.
machine-learning deep-learning c99 simd transformer moe avx2 quantization memory-efficient from-scratch systems-programming inference-engine mixture-of-experts zero-dependencies linear-attention cpu-inference llm llm-inference mxfp4 kimi-k3
Read and write spreadsheet files (CSV, XLSX and ODS), in a fast and scalable way
A fast, efficient universal vector embedding utility package.
python nlp fast machine-learning natural-language-processing word2vec word-embeddings embeddings gensim machine-learning-library glove vectors fasttext memory-efficient
A micro-library of stream components for building custom JSON and JSONC processing pipelines with a minimal memory footprint — parse, filter, and transform JSON far larger than available memory with a SAX-inspired token API, on Node.js or Web Streams.
nodejs parser json streaming stream pipeline filter tokenizer sax json-parser memory-efficient large-files streaming-json jsonc web-streams
Fastest and most memory efficient golang concurrent hashmap
An early-stage PHP parser designed for IDE usage scenarios.
Large Context Attention
A thread-safe queue faster and more resource efficient than golang's native channels
go golang optimization concurrency ringbuffer low-latency lock-free fastest high-throughput memory-efficient thread-safe spsc-queue mpsc-queue highly-concurrent zero-allocations zenq
Professional backend framework for Node.js
Implementation of a memory efficient multi-head attention as proposed in the paper, "Self-attention Does Not Need O(n²) Memory"
APOLLO: SGD-like Memory, AdamW-level Performance; MLSys'25 Oustanding Paper Honorable Mention
VGGT-X: When VGGT Meets Dense Novel View Synthesis
memory-efficient global-alignment 3d-reconstruction novel-view-synthesis 3dgs vggt 3d-foundation-model dense-view
Performance-oriented Data Structures for Kotlin
kotlin library performance datastructures high-performance efficiency kotlin-library data-structures memory-efficient memory-efficiency kotlin-libraries kotlin-data-structures
[CVPR 2025 Highlight] The official CLIP training codebase of Inf-CL: "Breaking the Memory Barrier: Near Infinite Batch Size Scaling for Contrastive Loss". A super memory-efficiency CLIP training scheme.
Easy Parallel Library (EPL) is a general and efficient deep learning framework for distributed model training.
deep-learning gpu memory-efficient data-parallelism model-parallelism distributed-training pipeline-parallelism
Fast and memory-efficient immutable collections and helper data structures
map performance immutable avl-tree functional-programming dictionary effects value-semantics persistent data-structures hashmap lock-free hashtable memory-efficient sum-types open-addressing compare-and-swap 2-3-tree reference-semantics robinhood-hashmap
Lightweight: Faster than light, Low on memory
Dragon: A Computation Graph Virtual Machine Based Deep Learning Framework.
Train Dense Passage Retriever (DPR) with a single GPU
Code for: "Social-Implicit: Rethinking Trajectory Prediction Evaluation and The Effectiveness of Implicit Maximum Likelihood Estimation" Accepted @ ECCV2022
real-time memory-efficient graph-convolutional-networks trajectory-prediction graph-neural-networks human-trajectory-prediction motion-forecasting motion-prediction pedestrian-trajectories spatio-temporal-graphs trajectory-forecasting gcnn-pedestrians social-implicit
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