A Former Apple Luminary Sets Out to Create the Ultimate GPU Software

Writing software for GPUs is also something of a “dark art,” says Waleed Atallah, the cofounder and CEO of Mako, a GPU kernel optimization company. “Mapping an algorithm to a GPU is an insanely difficult thing to do. There are a hundred million software devs, 10,000 who write GPU kernels, and maybe a hundred who can do it well.”

Mako is building AI agents to optimize coding for GPUs. Some developers think that’s the future for the industry, rather than building a universal compiler or a new programming language like Modular. Mako just raised $8.5 million in seed funding from Flybridge Capital and the startup accelerator Neo.

“We’re trying to take an iterative approach to coding and automate it with AI,” Atallah says. “By making it easier to write the code, you exponentially grow the number of people who can do that. Making another compiler is more of a fixed solution.”

Lattner notes that Modular also uses AI coding tools. But the company is intent on addressing the whole coding stack, not just kernels.

There are roughly 250 million reasons why investors think this approach is viable. Lattner is something of a luminary in the coding world, having previously built the open source compiler infrastructure project LLVM, as well as Apple’s Swift programming language. He and Davis are both convinced that this is a software problem that must be solved outside of a Big Tech environment, where most companies focus on building software for their own technology stack.

"When I left Google I was a little bit depressed, because I really wanted to solve this,” Lattner says. “What we realized is that it’s not about smart people, it’s not about money, it’s not about capability. It’s a structural problem.”

Munichiello shared a mantra common in the tech investing world: He says he’s betting on the founders themselves as much as their product. “He’s highly opinionated and impatient, and also right a lot of the time,” Munichiello said of Lattner. “Steve Jobs was also like that—he didn’t make decisions based on consensus, but he was often right.”