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Mojo and Building a CUDA Replacement with Chris Lattner
Manage episode 484149069 series 1418208
Content provided by Podcast Archives - Software Engineering Daily. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Podcast Archives - Software Engineering Daily or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
Python is the dominant language for AI and data science applications, but it lacks the performance and low-level control needed to fully leverage GPU hardware. As a result, developers often rely on NVIDIA’s CUDA framework, which adds complexity and fragments the development stack.
Mojo is a new programming language designed to combine the simplicity of Python with the performance of C and the safety of Rust. It also aims to provide a vendor-independent approach to GPU programming. Mojo is being developed by Chris Lattner, a renowned systems engineer known for his seminal contributions to computer science, including LLVM, the Clang compiler, and the Swift programming language.
Chris is the CEO and Co-Founder of Modular AI, the company behind Mojo. In this episode, he joins the show to discuss his engineering journey and his current work on AI infrastructure and the Mojo language.
Kevin Ball or KBall, is the vice president of engineering at Mento and an independent coach for engineers and engineering leaders. He co-founded and served as CTO for two companies, founded the San Diego JavaScript meetup, and organizes the AI inaction discussion group through Latent Space.
Sponsorship inquiries: [email protected]
The post Mojo and Building a CUDA Replacement with Chris Lattner appeared first on Software Engineering Daily.
875 episodes
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Manage episode 484149069 series 1418208
Content provided by Podcast Archives - Software Engineering Daily. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Podcast Archives - Software Engineering Daily or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
Python is the dominant language for AI and data science applications, but it lacks the performance and low-level control needed to fully leverage GPU hardware. As a result, developers often rely on NVIDIA’s CUDA framework, which adds complexity and fragments the development stack.
Mojo is a new programming language designed to combine the simplicity of Python with the performance of C and the safety of Rust. It also aims to provide a vendor-independent approach to GPU programming. Mojo is being developed by Chris Lattner, a renowned systems engineer known for his seminal contributions to computer science, including LLVM, the Clang compiler, and the Swift programming language.
Chris is the CEO and Co-Founder of Modular AI, the company behind Mojo. In this episode, he joins the show to discuss his engineering journey and his current work on AI infrastructure and the Mojo language.
Kevin Ball or KBall, is the vice president of engineering at Mento and an independent coach for engineers and engineering leaders. He co-founded and served as CTO for two companies, founded the San Diego JavaScript meetup, and organizes the AI inaction discussion group through Latent Space.
Sponsorship inquiries: [email protected]
The post Mojo and Building a CUDA Replacement with Chris Lattner appeared first on Software Engineering Daily.
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Similar to Podcast Archives - Software Engineering Daily
Technical interviews about software topics.
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…
continue reading
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continue reading
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