Hacker News with Generative AI: Performance Analysis

Hotspot: Linux `perf` GUI for performance analysis (github.com/KDAB)
This project is a KDAB R&D effort to create a standalone GUI for performance data. As the first goal, we want to provide a UI like KCachegrind around Linux perf. Looking ahead, we intend to support various other performance data formats under this umbrella.

Linux, Performance Analysis, Tools, GUI

104 points by jez 4 days ago | 17 comments

Doom GPU Flame Graphs (brendangregg.com)
AI Flame Graphs are now open source and include Intel Battlemage GPU support, which means it can also generate full-stack GPU flame graphs for providing new insights into gaming performance, especially when coupled with FlameScope (an older open source project of mine). Here's an example of GZDoom, and I'll start with flame scopes for both CPU and GPU utilization, with details annotated:

Open Source, Performance Analysis, Gaming

40 points by LorenDB 23 days ago | 12 comments

Yandex's High-Performance Profiler Is Now Open Source (medium.com)
Hello! Yesterday, we open-sourced Perforator, a continuous profiling system we use at Yandex, to analyze the performance of most of our services.

Open Source, Performance Analysis, Profiling Tools, Yandex

34 points by riv991 112 days ago | 1 comments

Yandex Open-Sources Perforator: Find Code Inefficiencies (phoronix.com)
Internet tech company Yandex announced the open-source release today of Perforator as a tool to help identify and evaluate code inefficiencies at scale.

Open Source, Software Development, Code Optimization, Performance Analysis

8 points by LorenDB 113 days ago | 0 comments

Two Parameter Model for Running Performance (normalizingconstant.com)
Human running performance from real-world big data is a super cool paper from 2020 that analyzes 14,000 people’s running activities.

Sports, Data Science, Machine Learning, Performance Analysis

7 points by brendanashworth 183 days ago | 0 comments

Metal-benchmarks: Apple GPU microarchitecture (github.com/philipturner)
This document thoroughly explains the Apple GPU microarchitecture, focusing on its GPGPU performance. Details include latencies for each ALU assembly instruction, cache sizes, and the number of unique instruction pipelines. This document enables evidence-based reasoning about performance on the Apple GPU, helping people diagnose bottlenecks in real-world software. It also compares Apple silicon to generations of AMD and Nvidia microarchitectures, showing where it might exhibit different performance patterns.