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Data Party THU
Data Party THU
May 16, 2026 · Artificial Intelligence

SubQ Beats Transformers: 12‑Million‑Token Context Model at Only 5% of Opus Cost

The article analyzes SubQ, a new LLM architecture using Subquadratic Sparse Attention (SSA) to achieve a 12‑million‑token context window with linear compute scaling, delivering up to 52× speedup and costing just 5% of Opus while matching dense‑attention performance on long‑context benchmarks.

Reinforcement LearningSSASubQ
0 likes · 14 min read
SubQ Beats Transformers: 12‑Million‑Token Context Model at Only 5% of Opus Cost
Taobao Frontend Technology
Taobao Frontend Technology
Feb 18, 2022 · Fundamentals

Unlock JavaScript Performance: From AST to Control Flow Graphs Explained

This article explores how understanding and visualizing JavaScript’s control and data flow—through abstract syntax trees, data flow graphs, and control flow graphs—can guide effective code optimization, illustrated with hardware-inspired examples and practical Arduino code, while also introducing SSA and Node Sea concepts.

ASTCode OptimizationControl Flow
0 likes · 13 min read
Unlock JavaScript Performance: From AST to Control Flow Graphs Explained
Tencent Cloud Developer
Tencent Cloud Developer
Sep 29, 2021 · Fundamentals

Building a Simple LLVM-Based Compiler: Lexer, Parser, SSA, Optimizer, JIT and Mutable Variables

The tutorial walks through building a complete LLVM‑based Kaleidoscope compiler—from a tokenizing lexer and recursive‑descent parser, through AST construction, LLVM IR generation with SSA and phi nodes, optimization passes, JIT execution, and mutable variable handling via stack allocation—providing full C++ source examples.

JITKaleidoscopeLLVM
0 likes · 47 min read
Building a Simple LLVM-Based Compiler: Lexer, Parser, SSA, Optimizer, JIT and Mutable Variables
Big Data Technology & Architecture
Big Data Technology & Architecture
Oct 25, 2020 · Backend Development

Understanding Value Numbering and Global Value Numbering in JVM C1 Compiler Optimization

This article explains how the JVM C1 compiler uses value numbering and global value numbering to merge identical computations, detailing hash calculation, ValueMapArray structures, control‑flow analysis, kill scenarios, and code transformation techniques for effective optimization.

Compiler OptimizationData Flow AnalysisGlobal Value Numbering
0 likes · 12 min read
Understanding Value Numbering and Global Value Numbering in JVM C1 Compiler Optimization