As of 2020's, it is basically a cheap/slow/simple CPU used in embedded system applications.
It is interpreted. It actually implements a Python (-like ?) interpreter that can run on a microcontroller. See e.g.: Compile MicroPython code for Micro Bit locally.
As a result, it is both very convenient, as it does not require a C toolchain to build for, but also very slow and produces larger images.
The first thing you must understand is the Classic RISC pipeline with a concrete example.
The good:
- slick UI! But very hard to read characters, they're way too small.
- attempts to show state diffs with a flash. But it goes by too fast, would be better if it were more permanent
- Reverse debugging
The bad:
The good:
- Reverse debugging
- circuit diagram
The bad:
- Clunky UI
- circuit diagram doesn't show any state??
Basically a synonym for central processing unit nowadays: electronics.stackexchange.com/questions/44740/whats-the-difference-between-a-microprocessor-and-a-cpu
It basically replaces a bunch of discrete digital components with a single chip. So you don't have to wire things manually.
Particularly fundamental if you would be putting those chips up a thousand cell towers for signal processing, and ever felt the need to reprogram them! Resoldering would be fun, would it? So you just do a over the wire update of everything.
Vs a microcontroller: same reason why you would want to use discrete components: speed. Especially when you want to do a bunch of things in parallel fast.
One limitation is that it only handles digital electronics: electronics.stackexchange.com/questions/25525/are-there-any-analog-fpgas There are some analog analogs, but they are much more restricted due to signal loss, which is exactly what digital electronics is very good at mitigating.
First FPGA experiences with a Digilent Cora Z7 Xilinx Zynq by Marco Reps (2018)
Source. Good video, actually gives some rationale of a use case that a microcontroller wouldn't handle because it is not fast enough.The History of the FPGA by Asianometry (2022)
Source. - github.com/ekondis/mixbench GPL
- github.com/ProjectPhysX/OpenCL-Benchmark custom non-commercial, non-military license
Example: github.com/cirosantilli/cpp-cheat/blob/d18a11865ac105507d036f8f12a457ad9686a664/cuda/inc.cu
Official hello world: github.com/ROCm/HIP-Examples/blob/ff8123937c8851d86b1edfbad9f032462c48aa05/HIP-Examples-Applications/HelloWorld/HelloWorld.cpp
Tested on Ubuntu 23.10 with P14s:TODO fails with:
sudo apt install hipcc
git clone https://github.com/ROCm/HIP-Examples
cd HIP-Examples/HIP-Examples-Applications/HelloWorld
make/bin/hipcc -g -c -o HelloWorld.o HelloWorld.cpp
clang: error: cannot find ROCm device library for gfx1103; provide its path via '--rocm-path' or '--rocm-device-lib-path', or pass '-nogpulib' to build without ROCm device library
make: *** [<builtin>: HelloWorld.o] Error 1Generic Ubuntu install bibliograpy:
The Coming AI Chip Boom by Asianometry (2022)
Source. - 2020: Traininum in 2020, e.g. techcrunch.com/2020/12/01/aws-launches-trainium-its-new-custom-ml-training-chip/
- 2018: AWS Inferentia, mentioned at en.wikipedia.org/wiki/Annapurna_Labs
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