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Releases: BioZig/biozig

BioZig v0.2.0

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@Sulkysubject37 Sulkysubject37 released this 10 Aug 08:48

BioZig v0.2.0

Core Architecture Advancements

SRFScheduler Integration: Formally implemented the Structural Recomputation Framework, enforcing strict $\mathcal{O}(L)$ memory bounds.
Deterministic OOM Panics: Replaced OS-level Out-of-Memory crashes with deterministic `SRF Memory Budget Exceeded` panics, guaranteeing stable DAG task execution via lock-free atomic arenas.
Unified Build Matrix: Multi-language versioning synchronized (`0.2.0`) across Zig core,

New Analytical Domains

ATLAZ Engine: Deployed topological engine for $H_1$ persistent homology and non-Euclidean recombination detection (`biozig atlaz`).

TiMSA Engine: Implemented topology-inspired multiple sequence alignment. Features the C++ Network Fusion Kernel (TiMSA/fuse_network.cpp) to fuse structural rigidity with statistical epistasis (biozig timsa). *

Standalone Binaries

Attached below are zero-dependency, statically cross-compiled binaries. Each archive contains the master biozig CLI as well as standalone timsa and atlaz tools:
Linux: x86_64, aarch64 (ARM), and riscv64 (Musl-static)
macOS: x86_64 (Intel) and aarch64 (Apple Silicon)
Windows: x86_64 (Intel/AMD) and aarch64 (Snapdragon/ARM)

BioZig v0.1.0

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@Sulkysubject37 Sulkysubject37 released this 10 Jul 09:09

BioZig v0.1.0

Version 0.1.0 defines the static memory boundary between biological data and hardware execution.

This deployment establishes the O(1) arena allocators and zero-copy parsers for Genomics, Structural Biology, Systems, and single-cell Transcriptomics. It finalizes the C-ABI boundary (libbiozig.so / .dll), enabling native matrix offloading for Python and R.

Standalone Binaries

BioZig is distributed as a set of fully static, native executables cross-compiled via Zig 0.16.0. (Note: 32-bit architectures are strictly unsupported due to physical address space limitations when memory-mapping large genomic datasets).

Attached are 64-bit binaries for: [Update includes ATLAZ binaries as well]

  • macOS: aarch64 (Apple Silicon), x86_64 (Intel)
  • Windows: x86_64 (64-bit)
  • Linux (musl): x86_64, aarch64, riscv64

(No external dependencies, Conda environments, or system libraries are required. Download the static binary for your architecture and execute directly.)


Creator and Curator: MD. Arshad (BioZig Software Foundation)
License: 3-Clause BSD