leo-gan/serialization
A hub for Serialization: theory, benchmarks, and 'gld' serializers that cover the 'misses'
Repositories
leo-gan/GLD.SerializerBenchmark
Serialization benchmarks (14 languages, ~20 standards, ~300 serializers), Compliance tests, Serialization 101–401 courses
leo-gan/gld-arrow-fortran
Fortran numeric arrays over the Arrow C Data Interface
leo-gan/gld-ion-kotlin
leo-gan/gld-ion-swift
From-scratch Amazon Ion serializer for Swift
leo-gan/gld-avro-swift
From-scratch Apache Avro for Swift
leo-gan/gld-avro-zig
From-scratch Apache Avro library for Zig
leo-gan/gld-arrow-zig
From-scratch Apache Arrow library for Zig
leo-gan/gld-ion-php
From-scratch Amazon Ion serializer for PHP
leo-gan/gld-arrow-php
From-scratch Apache Arrow IPC library for PHP
leo-gan/fpm-registry
Centralized registry of fpm packages
leo-gan/gld-hdf5
From-scratch HDF5, NetCDF, and ADIOS2 BP5 library for Mojo
leo-gan/gld-parquet
From-scratch Apache Parquet file library for Mojo
leo-gan/gld-arrow
From-scratch Apache Arrow columnar, IPC, and Flight library for Mojo
leo-gan/gld-smile
From-scratch Smile 1.0.7 library for Mojo
leo-gan/gld-protobuf
Protocol Buffers serializer for Mojo
leo-gan/gld-yaml
From-scratch YAML serializer for Mojo
leo-gan/gld-json
From-scratch JSON serializer for Mojo
leo-gan/gld-cbor
CBOR serializer for Mojo
leo-gan/gld-messagepack
From-scratch MessagePack library for Mojo
leo-gan/gld-flatbuffers
From-scratch FlatBuffers serializer for Mojo
leo-gan/gld-ion
From-scratch Amazon Ion 1.0 and 1.1 library for Mojo
leo-gan/gld-toml
From-scratch TOML 1.1 library for Mojo
leo-gan/onnxruntime
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
leo-gan/gld-bson
From-scratch BSON serializer for Mojo
leo-gan/gld-avro
Apache Avro serializer for Mojo
leo-gan/anonymizer
CLI, Web API, and an SDK anonymizing large PDF files, Excel, Word docs, CSVs
leo-gan/queue-benchmark
Multi-language benchmark for the queue libraries.
leo-gan/binary-optimizers
Different binary optimizers, including the "classical" STE optimizer
leo-gan/tallynet
TallyNet: each parameter is one bit; a tally weight is a group of bits counted for the layer.