Category: Research
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Tikz Trove
https://github.com/xiaohanyu/awesome-tikz https://github.com/PetarV-/TikZ neural network: https://tikz.net/neural_networks Neural Network 1D-2D Cross-Connection Visualization Keywords: Technical illustration, Network topology, Dimensional transition diagram, Feature transformation, Node connectivity visualization, Matrix representation A technical visualization demonstrating the dimensional transformation between 1D and 2D feature spaces in neural networks through an interconnected node matrix system. 2D Convolution Operation Visualization Keywords: Mathematical visualization, Convolution…
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ECE5505 Digital Test and Verification Final Project
overleaf project folder 0️⃣1️⃣A survey of digital circuit testing in the light of machine learning. 1 0️⃣2️⃣A Survey and Recent Advances: Machine Intelligence in Electronic Testing. 2 0️⃣3️⃣✅Machine intelligence for efficient test pattern generation.3 Backtracing: identifies PIs to assign to meet ATPG objectives (e.g., exciting or propagating faults). Backtracking: Backtracking is a class of algorithms…
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ECE5505 Digital Test and Verification Notes Part II
This blog serves as the 2nd and last part for the class ECE5505 Digital Test and Verification. D Flip Flop Delay/Data flip flop: The flip flop remains in its current state until its receives a signal like clock that switches it to opposite state. The clock single required for the synchronous version of D flip…
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Accelerate Pytorch
Use Pytorch to accelerate with GPU or apple silicon with Metal
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ECE5505 Digital Test and Verification Notes Part I
Introduction This is the blog for VT ECE5505 digital system test and verification course summary, it is currently working as a draft and not finalized. Simulations Fault Simulation Logic Sim Definition given a circuit, fault model, a test set, determine fault coverage determine test set qualityATPG, a vector 1️⃣Serial2️⃣Parallel-fault3️⃣Parallel-pattern4️⃣Deductive Fault Simulation5️⃣Concurrent6️⃣Critical Path Tracing7️⃣Statistical8️⃣Differential9️⃣Combined STAFAN Non-statistical…
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Mastering the Gumbel-Softmax Trick: Turning Hard Decisions into Smooth Learning
Introduction Imagine teaching a computer how to choose between different options — like picking the best movie recommendation or deciding which move to make in a game. These choices often boil down to picking one option from several, a process called categorical sampling. However, this kind of decision-making poses a challenge when training machine learning models…
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HotSpot Thermal Model Notes
Introduction Hotspot has been released to its 7 iteration with multiple updates regarding accurate thermal simulation benchmark. Installation To increase the simulation speed, the SUPERLU package is needed, depending on the various distros with own specifiic package managers, the installation could be different. Once it is installed, hotspot could be compiled. SuperLU I prefer to…
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Interact with Python virtual environment
Using python for mahcine learning projects is totally different from utilizing the language for productivity on daily tasks. Python official website provides the documentations for venv1. This post2 contains a comprehensive guide on how to use the virtual environment. There are lots of tutorials on how to setup, manage and dispose a python virtual environment…
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Ilya’s secret machine learning paper list
This link1 contains Ilya Sutskever’s2 curated machine learning paper list. The following tweets show the original story behind this list. I modified the sequence so that similar ones are grouped together, yet the original index with digit emojis is placed in the beginning of the paper title for your own reference, although I don’t think…
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Exploiting 2.5D/3D Heterogeneous Integration for AI Computing
References Exploiting 2.5D/3D Heterogeneous Integration for AI Computing1 Benchmarking Heterogeneous Integration with 2.5D/3D Interconnect Modeling2 End-to-End Benchmarking of Chiplet-Based In-Memory Computing3 Summary HISIM4, a modeling and benchmarking tool for heterogeneous integration of chiplets by communicating through NoP5. Components: partitioning, mapping and placement; computing unit/processing unit; heterogeneous interconnection; network/routing engine; thermal analysis. technology roadmap6, power/latency prediction,…
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A guide on how to use Advanced Research Computing at Virginia Tech
Virginia Tech provides computing resources for computing with is suitable for simulations, machine learning model training, which called Advanced Research Computing. It provides a user friendly guide on how to use its system, but I think it would be nicer to try to summarize the most essential ones when you want to use it in…