Update 2020-08-24-torchcsprng-release-blog.md

Author: wookim3

_posts/2020-08-24-torchcsprng-release-blog.md

@@ -4,10 +4,10 @@ title: 'PyTorch framework for cryptographically secure random number generation,
 author: Team PyTorch
 ---
 
-[torchcsprng](https://github.com/pytorch/csprng) is a PyTorch [C++/CUDA extension](https://pytorch.org/tutorials/advanced/cpp_extension.html) that provides [cryptographically secure pseudorandom number generators](https://en.wikipedia.org/wiki/Cryptographically_secure_pseudorandom_number_generator) for PyTorch.
-
 One of the key components of modern cryptography is the pseudorandom number generator. Katz and Lindell stated, "The use of badly designed or inappropriate random number generators can often leave a good cryptosystem vulnerable to attack. Particular care must be taken to use a random number generator that is designed for cryptographic use, rather than a 'general-purpose' random number generator which may be fine for some applications but not ones that are required to be cryptographically secure."[1] Additionally, most pseudorandom number generators scale poorly to massively parallel high-performance computation because of their sequential nature. Others don’t satisfy cryptographically secure properties.
 
+[torchcsprng](https://github.com/pytorch/csprng) is a PyTorch [C++/CUDA extension](https://pytorch.org/tutorials/advanced/cpp_extension.html) that provides [cryptographically secure pseudorandom number generators](https://en.wikipedia.org/wiki/Cryptographically_secure_pseudorandom_number_generator) for PyTorch.
+
 ## torchcsprng overview 
 
 Historically, PyTorch had only two pseudorandom number generator implementations: Mersenne Twister for CPU and Nvidia’s cuRAND Philox for CUDA. Despite good performance properties, neither of them are suitable for cryptographic applications. Over the course of the past several months, the PyTorch team developed the torchcsprng extension API. Based on PyTorch dispatch mechanism and operator registration, it allows the users to extend c10::GeneratorImpl and implement their own custom pseudorandom number generator.