accelerators

Lex Fridman interviews Chris Lattner, creator of LLVM, Clang and Swift, about compilers, Swift for TensorFlow, TPUs and ML accelerators. The talk covers how hardware and software meet to produce efficient code.

Chris Lattner's ASPLOS 2021 keynote on the golden age of compiler design in an era of hardware and software co-design, covering compiler infrastructure for accelerators and unifying hardware IRs.

Bill Dally of NVIDIA gives a Hot Chips 2023 keynote on the challenges of building hardware for deep learning. He traces how GPUs have been adapted for machine learning, especially training.

Dan Wood reviews the Vampire 2 FPGA accelerator for the Amiga 600. He covers how much faster it makes the machine and what it can run.

Jim Keller's talk at the 2020 Scaled Machine Learning conference on Moore's Law in the age of AI chips. He compares scalar, vector and GPU-style parallel approaches to computation.

Dave Plummer tours the IBM z16 mainframe from design through factory assembly, test lab, accelerators and water cooling. He explains why mainframes still exist and what makes them reliable.