Why GPUs Really Matter: From Architecture Basics to CUDA Programming

This article explains why GPUs have become the preferred platform for high‑performance computing, covering Dennard scaling, GPU speed advantages, theoretical FLOPS calculations, CUDA programming examples like SAXPY, the SIMT execution model, instruction pipelines, and modern techniques for handling branch divergence and register bank conflicts.

CUDA programmingGPU architectureGPU performance

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Why GPUs Really Matter: From Architecture Basics to CUDA Programming

Tencent Technical Engineering

Mar 21, 2025 · Fundamentals

Fundamentals of GPU Architecture and Programming

The article explains GPU fundamentals—from the end of Dennard scaling and why GPUs excel in parallel throughput, through CUDA programming basics like the SAXPY kernel and SIMT versus SIMD execution, to the evolution of the SIMT stack, modern scheduling, and a three‑step core architecture design.

CUDAGPUGPU programming

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Fundamentals of GPU Architecture and Programming

Architects' Tech Alliance

Oct 16, 2024 · Fundamentals

Unveiling GPU Architecture: From Compute Units to Rendering Pipelines

This article provides a comprehensive technical overview of modern GPU architecture, covering memory hierarchy, compute units, shader execution, rendering pipelines, and performance‑optimisation techniques such as unified shaders, SIMT, warp scheduling, and tile‑based rendering strategies.

GPUMemoryRendering

0 likes · 32 min read

Unveiling GPU Architecture: From Compute Units to Rendering Pipelines

Architects' Tech Alliance

Aug 21, 2024 · Fundamentals

Inside NVIDIA’s Stream Multiprocessor: How GPUs Execute Parallel Workloads

This article provides a detailed technical overview of the Stream Multi‑processor (SM) in modern GPUs, explaining its micro‑architecture, instruction fetch‑decode pipeline, warp scheduling, SIMT stack handling, scoreboard mechanisms, and strategies for hiding memory latency to maximize parallel execution efficiency.

GPUSIMTScoreboard

0 likes · 17 min read

Inside NVIDIA’s Stream Multiprocessor: How GPUs Execute Parallel Workloads

Architects' Tech Alliance

Mar 29, 2023 · Fundamentals

Stream Multiprocessor (SM) Architecture and Execution Pipeline in GPUs

This article provides a comprehensive overview of GPU stream multiprocessors, detailing their micro‑architecture, instruction fetch‑decode‑execute pipeline, SIMT/ SIMD organization, warp scheduling, scoreboard mechanisms, and techniques for handling thread divergence and deadlock in GPGPU designs.

GPUSIMTScoreboard

0 likes · 16 min read

Stream Multiprocessor (SM) Architecture and Execution Pipeline in GPUs