LEGO: The Open-Source Framework That Turns AI Loops into Silicon—No RTL Templates Required
3 hours ago 高效码农Keywords: LEGO accelerator, automatic RTL generation, spatial accelerator, tensor applications, AI chip design, Gemmini comparison, data-flow fusion, MIT Han Lab TL;DR LEGO is an open-source toolchain released by MIT Han Lab in 2025. Feed it a plain tensor loop (GEMM, Conv2D, Attention, MTTKRP) and it returns production-grade Verilog—no human-written templates, no HLS headaches. On a 28 nm test chip LEGO beats the state-of-the-art Gemmini generator by 3.2× speed and 2.4× energy while using the same MAC count and on-chip memory. What you will learn in 12 minutes Why even Google still hand-tunes TPU blocks—and where that hurts How LEGO removes …
Apple GPU Matrix Multiplication Acceleration Units: Revolutionizing AI Hardware Performance
8 days ago 高效码农Apple GPU Matrix Multiplication Acceleration Units: A Technical Breakthrough Reshaping AI Computing In today’s era of rapid artificial intelligence advancement, hardware acceleration capabilities have become a critical factor limiting the development of large-scale models. For AI developers worldwide, the performance of computing devices directly determines the efficiency of model training and inference. At Apple’s recent product launch event, a significant GPU upgrade attracted widespread attention from the technical community — Apple announced that its next-generation GPU will integrate matrix multiplication acceleration units. This change not only marks a strategic adjustment in Apple’s AI hardware strategy but also may reshape the …
CUDA-L1 Optimization Breakthrough: AI Redefines GPU Performance Standards
1 months ago 高效码农CUDA-L1: Revolutionizing GPU Performance Through Smart Code Optimization GPU server room with blue lighting The Growing Need for Faster GPUs The rapid growth of large language models (LLMs) has created an insatiable demand for GPU computing power. Training these massive AI systems requires thousands of specialized graphics processors working in parallel, driving up costs and energy consumption. Traditional methods of optimizing CUDA code—the programming language that powers NVIDIA GPUs—have hit their limits. Enter CUDA-L1, a breakthrough framework that uses artificial intelligence to automatically discover better ways to run code on GPUs. What Makes CUDA Optimization So Difficult? Writing efficient CUDA …