At NVIDIA. Languages, compilers, and APIs for real-time. DMs open for folks looking for advice/mentoring. She/her š³ļøāā§ļøš³ļøāš. Personal acct: @TessFactor.
The Wired
Joined October 2009
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The Slang project is seeking experienced GPU/graphics/AI compiler programmers who want to be part of the development of an ecosystem for AI-powered real-time graphics. My DMs are open.
New #NVIDIAResearch paper: SLANG.D: Fast, Modular and Differentiable Shader Programming: shows how a single language serves as a unified platform for real-time, inverse, and differentiable rendering.
Collaboration with @MIT, @UCSanDiego, & @UW.
š§µ 1/2
nvda.ws/46H4p14
Theresa Foley retweeted
New #NVIDIAResearch paper: SLANG.D: Fast, Modular and Differentiable Shader Programming: shows how a single language serves as a unified platform for real-time, inverse, and differentiable rendering.
Collaboration with @MIT, @UCSanDiego, & @UW.
š§µ 1/2
nvda.ws/46H4p14
Theresa Foley retweeted
Bringing autodiff to shaders is a challenging task. It takes years of effort to design the language that integrates differentiation as a first-class citizen, allowing autodiff to work seamlessly with custom types, arbitrary control flow, generics and dynamic dispatch.
New #NVIDIAResearch paper: SLANG.D: Fast, Modular and Differentiable Shader Programming: shows how a single language serves as a unified platform for real-time, inverse, and differentiable rendering.
Collaboration with @MIT, @UCSanDiego, & @UW.
š§µ 1/2
nvda.ws/46H4p14
Theresa Foley retweeted
It is traditional for programmers to measure our ages in hexadecimal. Today I became 2B, so it only seemed appropriateā¦
ALT Itās me in cosplay as 2B.
Theresa Foley retweeted
(1/5) Shading language and real-time rendering innovation are inextricably tied together.
In this new talk, Slang researcher, Yong He, describes the details of new language features in Slang, and how they are used by real-time path tracing researchers.
youtu.be/DUOn9ek0bdI
Theresa Foley retweeted
We've been co-researching shading language and real-time rendering innovation for years.
@TangentVector's recent talk describes the Slang journey from research to production.
Folks who would like to learn more about the Slang shading language and our experiences deploying it at NVIDIA can check out the recording of my talk at the LLVM WiCT meetup: youtu.be/XDJdHKIY06E
Anybody who is excited about the possibilities of Slang can contact me by email/DM. Collaborators are welcome, and also we are hiring: nvidia.wd5.myworkdayjobs.comā¦
Folks who would like to learn more about the Slang shading language and our experiences deploying it at NVIDIA can check out the recording of my talk at the LLVM WiCT meetup: youtu.be/XDJdHKIY06E
Theresa Foley retweeted
(1/10) Slides + Recording of Petrik Clarbergās GDC/GTC real-time path tracing research talk are now available online #GDC2022 #GTC22
research.nvidia.com/publicatā¦
The renewed conversations around dxc and DXIL are also relevant context for me.
The dxc and Slang projects started at similar times, one based on clang/LLVM and the other not. The trade-offs involved in such decisions are nuanced.
We are in subtweet-of-a-subtweet territory, and many of us are stuck vaguely alluding to compilers we have worked on/with at various companies, because we arenāt allowed talk specifics. Part of what I saw was talking about the Mesa stack and its āNIR.ā
The perception of safety can lead people to ignore the technical reasons why an idea may be less favorable (like the āunstable IRā issue). Part of my point is that people arenāt necessarily wrong to do so, given the political aspects of growing a project.
LLVM being seen as a āsafeā bet is part of why SPIR happened despite warnings from people like me about the instability issue.
I suspect dxc was built on top of clang in part because it was seen as āsafe,ā and yet here we are as an industry discussing a re-do on that effort.
I can attest to the flip side being challenging. If you are sure that the āsafeā choice is not the right one for your project, do not expect immediate buy-in and be prepared to do the hard work of explaining and justifying your choice.
It helps that both LLVM and clang are great technologies with strong communities. They are seldom an outright *bad* choice when they get used.