How Deepseek Destroyed OpenAI, and How You Can Do it Too!

Author(s): Mohit Varikuti

Originally published on Towards AI.

What is PTX/ASM?

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In the rapidly evolving world of GPU computing, performance can often be the make-or-break factor in an application’s success. One of the secret weapons behind high-performance frameworks like DeepSeek is the intelligent use of CUDA PTX and inline assembly (ASM). DeepSeek’s remarkable efficiency and speed didn’t come solely from high-level algorithm design; it was also the way DeepSeek got so good by exploiting low-level CUDA PTX/ASM optimizations to squeeze every ounce of performance from modern GPUs.

In this article, we’ll dive into CUDA’s PTX (Parallel Thread Execution) language and explore how inline assembly can be used within CUDA kernels. We’ll look at what PTX is, how it fits into the CUDA compilation pipeline, and examine some practical code examples.

CUDA PTX is an intermediate assembly-like language used by NVIDIA GPUs. Think of PTX as the “assembly language” for CUDA, though it’s higher-level than the actual machine code executed on the GPU. When you compile CUDA code using nvcc, your high-level C/C++ code is transformed into PTX code, which is then optimized and further compiled down to machine-specific binary code (SASS) for the target GPU, more specifically:

Portability: PTX abstracts many hardware details,… Read the full blog for free on Medium.

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Published via Towards AI