Title: *Common Lisp go brrt: Achieving Near C/C++ Performance with Lupus* * *0:26**:* *Goal:* The speaker, Marco Heisig, aims to demonstrate the speed improvements possible in Common Lisp for numerical computation, specifically focusing on a Jacobi iteration example. * *1:44**:* *Initial Performance:* A standard Common Lisp implementation of a Jacobi iteration using loops achieves about 840 megaflops, comparable to JavaScript. * *2:57**:* *Optimization with "Lupus":* By replacing standard loops with a custom "Lupus" implementation, the performance jumps to 16 gigaflops, a ~20x speedup. * *3:39**:* *Key Takeaway:* The Lupus approach achieves near-C/C++ performance without resorting to complex code changes or sacrificing code clarity. It leverages AVX2 instructions for vectorized operations. * *4:37**:* *"Common Lisp go brrt":* The title and final demonstration playfully highlight the significant speed boost achieved, showcasing Common Lisp's potential for high-performance computing. * *0:00**:* *Context:* This was a lightning talk at the European Lisp Symposium 2022, demonstrating the Lupus project. I used gemini-1.5-pro-exp-0801 to summarize the transcript. Cost (if I didn't use the free tier): $0.02 Input tokens: 4650 Output tokens: 474
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Title: *Common Lisp go brrt: Achieving Near C/C++ Performance with Lupus*
* *0:26**:* *Goal:* The speaker, Marco Heisig, aims to demonstrate the speed improvements possible in Common Lisp for numerical computation, specifically focusing on a Jacobi iteration example.
* *1:44**:* *Initial Performance:* A standard Common Lisp implementation of a Jacobi iteration using loops achieves about 840 megaflops, comparable to JavaScript.
* *2:57**:* *Optimization with "Lupus":* By replacing standard loops with a custom "Lupus" implementation, the performance jumps to 16 gigaflops, a ~20x speedup.
* *3:39**:* *Key Takeaway:* The Lupus approach achieves near-C/C++ performance without resorting to complex code changes or sacrificing code clarity. It leverages AVX2 instructions for vectorized operations.
* *4:37**:* *"Common Lisp go brrt":* The title and final demonstration playfully highlight the significant speed boost achieved, showcasing Common Lisp's potential for high-performance computing.
* *0:00**:* *Context:* This was a lightning talk at the European Lisp Symposium 2022, demonstrating the Lupus project.
I used gemini-1.5-pro-exp-0801 to summarize the transcript.
Cost (if I didn't use the free tier): $0.02
Input tokens: 4650
Output tokens: 474
Awesome.