Thx to @cpu_design
Author — Rahul B. at Tenstorrent
"Here’s my list of 5 papers you should read to learn about Out-of-Order Processors!"

#1 The Microarchitecture of Superscalar Processors by James E. Smith and Gurindar S. Sohi

— Touches on every aspect of superscalar processor design and does an excellent job explaining concepts like register renaming, instruction scheduling, and memory operations.

https://course.ece.cmu.edu/~ece447/s15/lib/exe/fetch.php?media=00476078.pdf

#2 The Alpha 21264 Microprocessor by R. E. Kessler

— Explains the instruction fetch, branch prediction, out-of-order execution, instruction retire and exceptions and the internal memory system for the Alpha 21264 processor.

https://course.ece.cmu.edu/~ece447/s15/lib/exe/fetch.php?media=kessler_-_1999_-_the_alpha_21264_microprocessor.pdf

#3 Implementing Precise Interrupts in Pipelined Processors by James E. Smith and Andrew R. Pleszkun

— This paper does a great job at describing and evaluating solutions to the precise interrupt problem in pipelined processors.

https://course.ece.cmu.edu/~ece447/s15/lib/exe/fetch.php?media=00004607.pdf

#4 Checkpoint Repair for Out-of-order Execution Machines by Wen-mei W. Hwu and Yale N. Patt

— Discusses the several properties for the checkpoint repair mechanism to reset the processor state to a known previous state.

https://course.ece.cmu.edu/~ece447/s15/lib/exe/fetch.php?media=p18-hwu.pdf

#5 A case for (partially) TAgged GEometric history length branch prediction by André Seznec and Pierre Michaud

— This paper provides an excellent introduction to TAGE predictors, covering all relevant terminology along with hardware implementation details.

https://www.irisa.fr/caps/people/seznec/JILP-COTTAGE.pdf

https://www.techradar.com/pro/microsoft-backed-a-tiny-hardware-startup-that-just-launched-its-first-ai-processor-that-does-inference-without-gpu-or-expensive-hbm-memory-and-a-key-nvidia-partner-is-collaborating-with-it

*I'm excited to share a sneak peek of our latest work at Intel Corporation —
a groundbreaking approach to Electronic Design Automation (EDA) that integrates intelligent design agents into the engineering workflow.

Our agent, trained on massive datasets from the best of our engineers, provides real-time insights and solutions within the EDA tools, enabling the solving of tasks ranging from simple to complex multi-iteration challenges, making the design process more efficient and innovative.

This demo utilizes The OpenROAD Project, an open-source EDA tool developed by The Regents of the University of California.

url: https://www.linkedin.com/posts/itai-yeshurun_intel-eda-llm-ugcPost-7267911435886682112-IIhh

Let it be here. Life lessons from one of the greatest computer scientists.
https://cacm.acm.org/opinion/life-lessons-from-the-first-half-century-of-my-career/

https://arxiv.org/abs/2409.03384

#MTIA
https://engineering.fb.com/2024/08/22/ml-applications/meta-mtia-hardware-co-design/

https://www.cnbc.com/video/2024/08/23/how-google-makes-custom-cloud-chips-that-power-apple-ai-and-gemini.html

#BlockFP #FPGA #LLM
https://myrtle.ai/resources/llama3-blockfloat16-quantization/

RISC-V Ecosystem Panel | Open Source is Transforming AI and Hardware

https://www.youtube.com/watch?v=hQfmT_LM-zY

Exploring logic synthesis with Yosys
https://www.linkedin.com/posts/ashwinrajesh_a-guide-to-logic-synthesis-using-yosys-ugcPost-7221574339165396993-6sN5
56-pages doc: https://drive.google.com/file/d/13ER2Jb7fj6pUIeCzoba837SHPWG-xX-Y/view