ternlang-core 1.2.5

Compiler and VM for Ternlang — balanced ternary language with affirm/tend/reject trit semantics, @sparseskip codegen, and BET bytecode execution.
Documentation 
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//! WebAssembly (Wasm) Edge Domination via v128 SIMD
//!
//! The future of agentic AI dictates execution at the browser edge, ensuring privacy 
//! and eliminating exorbitant bandwidth costs. This module utilizes specific Wasm v128 
//! instructions to pack highly compressed ternary weights into SIMD lanes.
//! 
//! By compressing AI memory arrays (demonstrating up to 65% savings on session memory 
//! and 58% on LLM system prompts), the Wasm-compiled Albert Agent can operate 
//! autonomously with an exceptionally low memory footprint.

#[cfg(target_arch = "wasm32")]
use core::arch::wasm32::*;

/// Float Vector Addition: Executing continuous 4-lane tensor accumulations.
#[cfg(target_arch = "wasm32")]
pub unsafe fn execute_tensor_accumulation(a: v128, b: v128) -> v128 {
    f32x4_add(a, b)
}

/// Integer Packing: Processing 16 concurrent {-1, 0, +1} quantized weights.
#[cfg(target_arch = "wasm32")]
pub unsafe fn pack_quantized_weights(a: v128, b: v128) -> v128 {
    i8x16_add(a, b)
}

/// Logic Inversion: Accelerating ambiguity detection via bitwise inverse logic.
#[cfg(target_arch = "wasm32")]
pub unsafe fn accelerate_ambiguity_detection(a: v128, b: v128) -> v128 {
    v128_andnot(a, b)
}

/// Vector Initialization: Initializing SIMD lanes for BET VM execution.
#[cfg(target_arch = "wasm32")]
pub unsafe fn init_ternary_vector() -> v128 {
    f32x4_splat(0.0) // using splat for initialization as const is a macro
}