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Signed-off-by: Jianliang Shen <[email protected]>
Jianliang-Shen · Jul 18, 2024 · c6f6f61 · c6f6f61
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diff --git a/source/_posts/GPU/Arch.md b/source/_posts/GPU/Arch.md
@@ -224,7 +224,9 @@ CUDA Core 专门处理图形工作负载，Tensor Core 更擅长处理数字工
 
 ### Fermi 架构
 
-[Fermi架构白皮书](https://www.nvidia.com/content/PDF/fermi_white_papers/NVIDIA_Fermi_Compute_Architecture_Whitepaper.pdf)
+<!-- [Fermi架构白皮书](https://www.nvidia.com/content/PDF/fermi_white_papers/NVIDIA_Fermi_Compute_Architecture_Whitepaper.pdf) -->
+
+<iframe src="https://www.nvidia.com/content/PDF/fermi_white_papers/NVIDIA_Fermi_Compute_Architecture_Whitepaper.pdf" width="100%" height="800" name="topFrame" scrolling="yes"  noresize="noresize" frameborder="0" id="topFrame"></iframe>
 
 Fermi 是 Nvidia 在 2010 年发布的架构，引入了很多今天也仍然不过时的概念。英伟达第一个采用 GPU-Direct 技术的 GPU 架构，它拥有 32 个 SM（流多处理器）和 16 个 PolyMorph Engine 阵列。该架构采用了 4 颗芯片的模块化设计，拥有 32 个光栅化处理单元和 16 个纹理单元，搭配 GDDR5 显存。
 
@@ -266,6 +268,8 @@ SM 内还有 16 个 LD/ST 单元，也就是 Load/Store 单元，支持 16 个
 
 [2014 Maxwell架构白皮书](https://developer.nvidia.com/maxwell-compute-architecture)
 
+<!-- <iframe src="https://developer.nvidia.com/maxwell-compute-architecture" width="100%" height="800" name="topFrame" scrolling="yes"  noresize="noresize" frameborder="0" id="topFrame"></iframe> -->
+
 ![](/img/post_pics/gpu/arch/12.png)
 
 Maxwell的 SM 开始做减法了，每个 SM（SMM）中包含：
@@ -324,7 +328,9 @@ Tesla微观架构总览图如上。下面将阐述它的特性和概念：
 
 ### Volta 架构
 
-[Volta白皮书](https://images.nvidia.cn/content/volta-architecture/pdf/volta-architecture-whitepaper.pdf)
+<!-- [Volta白皮书](https://images.nvidia.cn/content/volta-architecture/pdf/volta-architecture-whitepaper.pdf) -->
+
+<iframe src="https://images.nvidia.cn/content/volta-architecture/pdf/volta-architecture-whitepaper.pdf" width="100%" height="800" name="topFrame" scrolling="yes"  noresize="noresize" frameborder="0" id="topFrame"></iframe>
 
 ![](/img/post_pics/gpu/arch/14.png)
 
@@ -337,7 +343,9 @@ Tesla微观架构总览图如上。下面将阐述它的特性和概念：
 
 ### Turing架构
 
-[2018Turing架构白皮书](https://www.nvidia.com/content/dam/en-zz/Solutions/design-visualization/technologies/turing-architecture/NVIDIA-Turing-Architecture-Whitepaper.pdf)
+<!-- [2018Turing架构白皮书](https://www.nvidia.com/content/dam/en-zz/Solutions/design-visualization/technologies/turing-architecture/NVIDIA-Turing-Architecture-Whitepaper.pdf) -->
+
+<iframe src="https://www.nvidia.com/content/dam/en-zz/Solutions/design-visualization/technologies/turing-architecture/NVIDIA-Turing-Architecture-Whitepaper.pdf" width="100%" height="800" name="topFrame" scrolling="yes"  noresize="noresize" frameborder="0" id="topFrame"></iframe>
 
 ![](/img/post_pics/gpu/arch/15.png)
 
@@ -355,7 +363,9 @@ Turing架构采用全新SM设计，每个TPC均包含两个SM，每个SM共有64
 
 ### Ampere 架构
 
-[Ampere架构白皮书](https://images.nvidia.cn/aem-dam/en-zz/Solutions/data-center/nvidia-ampere-architecture-whitepaper.pdf)
+<!-- [Ampere架构白皮书](https://images.nvidia.cn/aem-dam/en-zz/Solutions/data-center/nvidia-ampere-architecture-whitepaper.pdf) -->
+
+<iframe src="https://images.nvidia.cn/aem-dam/en-zz/Solutions/data-center/nvidia-ampere-architecture-whitepaper.pdf" width="100%" height="800" name="topFrame" scrolling="yes"  noresize="noresize" frameborder="0" id="topFrame"></iframe>
 
 代表产品为 GeForce RTX 30 系列。该架构继续优化并行计算能力，并引入了更先进的 GDDR6X 内存技术，大幅提高了内存带宽和性能。相比 Turing 架构，Ampere 架构中的 SM 在 Turing 基础上增加了一倍的 FP32 运算单元，这使得每个 SM 的 FP32 运算单元数量提高了一倍，同时吞吐量也就变为了一倍。此外，安培架构还改进了着色器性能和张量核（Tensor Cores），进一步加速深度学习和人工智能任务的处理速度。
 
@@ -388,8 +398,9 @@ NVIDIA A100基于7nm Ampere GA100 GPU，具有6912 CUDA内核和432 Tensor Core
 ![](/img/post_pics/gpu/arch/18.png)
 
 [Hopper架构白皮书](https://resources.nvidia.com/en-us-tensor-core?ncid=no-ncid)
-[Hopper中文架构白皮书](https://resources.nvidia.com/cn-hopper-architecture?ncid=no-ncid)
+<!-- [Hopper中文架构白皮书](https://resources.nvidia.com/cn-hopper-architecture?ncid=no-ncid) -->
 
+<iframe src="https://resources.nvidia.com/cn-hopper-architecture?ncid=no-ncid" width="100%" height="800" name="topFrame" scrolling="yes"  noresize="noresize" frameborder="0" id="topFrame"></iframe>
 
 作为面向专业计算的GPU，H100采用HBM3高带宽显存，NVIDIA将六颗HBM3高带宽显存堆栈在核心两侧。核心内建5120-bit的HBM3显存位宽，英伟达可配置最高80GB显存，SXM5版（HBM3显存）带宽更是达到3TB/s，PCIe版本（HBM2e）则是2TB/s。
 
@@ -402,5 +413,6 @@ H100的主机接口同样迎来升级，SXM外形的PCB板配备新一代NVLink
 ### Blackwell 架构
 
 [Blackwell 架构](https://www.nvidia.cn/data-center/technologies/blackwell-architecture/)
-[白皮书](https://resources.nvidia.com/en-us-blackwell-architecture?ncid=no-ncid)
+<!-- [白皮书](https://resources.nvidia.com/en-us-blackwell-architecture?ncid=no-ncid) -->
 
+<iframe src="https://resources.nvidia.com/en-us-blackwell-architecture?ncid=no-ncid" width="100%" height="800" name="topFrame" scrolling="yes"  noresize="noresize" frameborder="0" id="topFrame"></iframe>
diff --git a/source/_posts/GPU/Computing-Startup.md b/source/_posts/GPU/Computing-Startup.md
@@ -48,9 +48,14 @@ categories:
 | [Pytorch Examples](https://github.com/pytorch/examples)| 围绕 pytorch 的视觉、文本、强化学习等方面的一组示例。 |
 | [Pytorch 源码仓库](https://github.com/pytorch/pytorch)| 具有强大 GPU 加速的 Python 张量和动态神经网络。 |
 
+<iframe src="https://pytorch.org/tutorials/beginner/basics/intro.html" width="100%" height="800" name="topFrame" scrolling="yes"  noresize="noresize" frameborder="0" id="topFrame"></iframe>
+
 ### Cuda
 
 [CUDA 官方文档](https://docs.nvidia.com/cuda/)
+
+<iframe src="https://docs.nvidia.com/cuda/" width="100%" height="800" name="topFrame" scrolling="yes"  noresize="noresize" frameborder="0" id="topFrame"></iframe>
+
 [CUDA Runtime API](https://docs.nvidia.com/cuda/cuda-runtime-api/index.html)
 [CUDA Samples](https://github.com/NVIDIA/cuda-samples)
 

diff --git a/source/_posts/SW/AIoT/R329模型仿真测试.md → source/_posts/SW/AIoT/R329-AI-Model-Test.md b/source/_posts/SW/AIoT/R329模型仿真测试.md → source/_posts/SW/AIoT/R329-AI-Model-Test.md
diff --git a/source/_posts/SW/AIoT/R329-Debian系统安装体验.md → source/_posts/SW/AIoT/R329-Debian-Install.md b/source/_posts/SW/AIoT/R329-Debian系统安装体验.md → source/_posts/SW/AIoT/R329-Debian-Install.md
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diff --git a/source/_posts/SW/OS/STM32-Free-RTOS实战.md → source/_posts/SW/OS/STM32-Free-RTOS.md b/source/_posts/SW/OS/STM32-Free-RTOS实战.md → source/_posts/SW/OS/STM32-Free-RTOS.md
diff --git a/source/_posts/SW/OS/STM32-RT-Thread-OS实战.md → source/_posts/SW/OS/STM32-RT-Thread-O.md b/source/_posts/SW/OS/STM32-RT-Thread-OS实战.md → source/_posts/SW/OS/STM32-RT-Thread-O.md
diff --git a/source/_posts/SW/OS/socket进程间通信及喂狗框架.md → source/_posts/SW/OS/Socket-IPC-Watch-Dog.md b/source/_posts/SW/OS/socket进程间通信及喂狗框架.md → source/_posts/SW/OS/Socket-IPC-Watch-Dog.md
diff --git a/source/_posts/SW/OS/基于TCP-IP网络socket通信.md → source/_posts/SW/OS/TCP-IP-Socket-IPC.md b/source/_posts/SW/OS/基于TCP-IP网络socket通信.md → source/_posts/SW/OS/TCP-IP-Socket-IPC.md
diff --git a/source/_posts/SW/OS/vscode-wsl开发环境配置.md → source/_posts/SW/OS/VScode-WSL.md b/source/_posts/SW/OS/vscode-wsl开发环境配置.md → source/_posts/SW/OS/VScode-WSL.md
diff --git a/.../_posts/SW/OS/Windows系统配置Linux子系统开发ARM.md → source/_posts/SW/OS/WSL-Arm-Linux.md b/.../_posts/SW/OS/Windows系统配置Linux子系统开发ARM.md → source/_posts/SW/OS/WSL-Arm-Linux.md
diff --git a/source/_posts/SW/PCI设备驱动.md → source/_posts/SW/PCIe-Driver.md b/source/_posts/SW/PCI设备驱动.md → source/_posts/SW/PCIe-Driver.md
diff --git a/source/_posts/SW/使用qemu来debug.md → source/_posts/SW/Qemu-Debug.md b/source/_posts/SW/使用qemu来debug.md → source/_posts/SW/Qemu-Debug.md
diff --git a/source/_posts/Security/Chinese-Confidential-Compute-Standard.md b/source/_posts/Security/Chinese-Confidential-Compute-Standard.md
@@ -19,6 +19,7 @@ categories:
 
 原文：[Information security techniques-General framework for confidential computing](https://www.tc260.org.cn/file/2023-04-28/e9d12373-73ee-47e9-9ca0-8bddd02f27f0.pdf)
 
+<iframe src="https://www.tc260.org.cn/file/2023-04-28/e9d12373-73ee-47e9-9ca0-8bddd02f27f0.pdf" width="100%" height="1000" name="topFrame" scrolling="yes"  noresize="noresize" frameborder="0" id="topFrame"></iframe>
 
 ## 目录
Original file line number	Diff line number	Diff line change
Expand Up		@@ -19,6 +19,7 @@ categories:

		原文：[Information security techniques-General framework for confidential computing](https://www.tc260.org.cn/file/2023-04-28/e9d12373-73ee-47e9-9ca0-8bddd02f27f0.pdf)

		<iframe src="https://www.tc260.org.cn/file/2023-04-28/e9d12373-73ee-47e9-9ca0-8bddd02f27f0.pdf" width="100%" height="1000" name="topFrame" scrolling="yes" noresize="noresize" frameborder="0" id="topFrame"></iframe>

		## 目录

Expand Down