profiling

Go 1.27 introduces a goroutine leak profiler to accurately detect and prevent goroutine leaks in running programs, including production systems, with minimal false positives.

The article investigates why Arrays.fill is 265 times slower on G1GC compared to ParallelGC, tracing the issue to JIT-generated code and memory barriers through detailed profiling and assembly analysis.

Aiki Alpha 3 is released with substantial performance improvements, including cheaper runtime realization, adaptive number representations, enhanced profiling and coverage, and stricter library constraints.

FleetSieve introduces a decision-critical profiling method for SLO-aware LLM fleet configuration that optimizes resource allocation by reducing unnecessary measurements, achieving efficiency gains over uniform profiling.

A software engineer reflects on how scientists often lack software engineering skills, using an example of optimizing an astrophysics simulation postprocessing tool and advocating for a 'missing semester' for scientists.

An open-source tool called XProf Cubism Reducer reduces TensorBoard trace sizes by over 90% for JAX/XLA, making performance profiling more efficient.

This article demonstrates how to profile eBPF code performance by creating a simple C test harness that measures file open latency, enabling developers to compare overhead before and after attaching eBPF hooks.

Two official PyTorch tutorials linking to the 'Profiling in PyTorch' series are highlighted, providing guidance on using the PyTorch profiler API for performance debugging.

CodeSizer is a static code size profiling tool for embedded firmware that uses objdump and addr2line to attribute code size to inline call trees and generates an HTML report.

A beginner-friendly guide to using torch.profiler in PyTorch for profiling and optimizing deep learning workloads, covering trace reading, CUDA analysis, and torch.compile integration.

This tutorial demonstrates how to profile various attention implementations in PyTorch, from naive attention to scaled dot-product attention with different backends, using the PyTorch profiler on an NVIDIA A100 GPU.

A deep dive into Go's profiling mechanism, explaining how the runtime collects CPU, heap, block, mutex, and goroutine profiles, and how they are represented in the pprof format.

The article explores how agent tools are being used to encode development workflows for SGLang, turning debugging, benchmarking, and profiling into executable skills and reproducible experiments, with efforts like KDA-Pilot already producing merged PRs.

The paper introduces VirtueMap, a framework that profiles large language models by evaluating their rankings of ethical dilemma responses through an Aristotelian virtue ethics lens, using a validated common-sense ground truth.

A half-day tutorial at ISC High Performance 2026 on using compiler-assisted tools (FPChecker/LLVM) for floating-point error analysis and profiling in C/C++ scientific codes.

KernelPro is a closed-loop multi-agent system that uses LLMs and micro-profiling tools to automatically optimize GPU kernel code, achieving geomean speedups of 2.42×/4.69×/5.30× on KernelBench and demonstrating a measured 11.6% energy reduction at matched speed.

Introduces SocialPersona, a benchmark for evaluating multimodal large language models on their ability to recover revealed preferences from longitudinal social-media timelines and use them in personalized dialogue.

Analysis showing that GPUs used for AI training often sit idle waiting for data, questioning the severity of the GPU shortage.

The author shares excitement about kernel fusion and demonstrates using HuggingFace's kernels project to profile a GeGLU FFN fused Liger kernel, noting the profile's beauty.

Announces Part 2 of a profiling tutorial covering linear layer tracing, gemm epilogues, MLP tracing, and comparisons of torch compile vs Liger kernels, with a link to the full content.