weixin_44604698的博客

This paper mainly contributes the following 2 points:So the core logic the algorithm.

TileLang closely resembles TVM: it cleanly separates the scheduling space—thread binding, layout, tensorization, and pipelining—from the pure data-flow description, and it exposes the same knobs through the Python API shown in Fig. 1.As illustrated in Fig.

TVM can process graph-level and operator-level optimization.As for the graph-level optimization, it can do operator fusion, constant folding, static memory pre-allocation, and data transformate pass.Now I want emphasis operator fusion, It split the operato

This paper proposed a very simple method for parallel computation of large matrices. The following graph describes the core logic:A is splited by column, and B is splited by rows. Each shard of XA in MLP ,and each group consisting of Q1, K1, V1, is placed

The Triton is composed of 3 parts: Triton-C, Trion-IR and Triton JIT.1.1. The get_global_range(axis) is associated with kernel, and it is shown in the above graph.1.2. broadcastThe structure of Trion-IR is similar with MLIR. Both includes modules, func

【代码】MLIR: A Compiler Infrastructure for the End of Moore‘s Law。

I think there are 3 advantages in SGLang. It allows direct programing in python, it suuport RadixAttention to effeicient KVCache reuse, and it used compressed finite state machine to accelerate the structured output.Reuse the KVCache with the same prompts.

Kimi is the most frequently used large language model tool by me. It is faster than other tools, like deepseek. So I decide to read this paper to figure out the magic behind its chat interface.As a MaaS provider, there are a lot of constraints, limited re

建立对象池，可以避免对象的频繁构造与析构，同时防止内存碎片。

​通过参考eigen，实现了自己的一个表达式模板，目前可以完成加法和减法运算，并预留了其他运算的接口。主要优化技巧有：1、head only：只有头文件，使用方便；2、运用栈存储元素；3、运用表达式模板进行lazy compute，减少访存和临时变量生成；4、对赋值进行循环展开。​