performance

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#performance

Profile-guided optimization in Go

Lobsters Hottest · 4d ago Cached

Daniel Lemire benchmarks profile-guided optimization (PGO) in Go, showing modest speedups of 2-5% when parsing JSON, with the best gains when the training profile matches the workload.

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#performance

What garbage collection actually costs

Hacker News Top · 4d ago Cached

A technical article explains the true performance costs of garbage collection, contrasting tracing GCs, reference counting, and compile-time memory management in languages like Go, Java, Rust, Swift, and Python.

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#performance

Windows 11's built-in Weather app wastes more than 1 GB of RAM

Hacker News Top · 4d ago Cached

Windows 11's built-in Weather app can consume over 1 GB of RAM, about five times more than macOS's Weather app, due to its WebView2-based non-native architecture. This could noticeably impact lower-end PCs with 8-16 GB of RAM.

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#performance

@tom_doerr: httptap is a Python CLI that breaks HTTP requests down into specific phases like DNS resolution, TCP connection, TLS ha…

X AI KOLs Timeline · 5d ago Cached

httptap is a Python CLI that dissects HTTP requests into phases like DNS, TCP, TLS, and data transfer to generate detailed waterfall timelines for troubleshooting and performance analysis.

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#performance

enabling PCI-E p2p for consumer Nvidia cards will yield you more than you think

Reddit r/LocalLLaMA · 5d ago

Enabling PCI-E peer-to-peer (P2P) for consumer Nvidia GPUs with patched drivers and vLLM environment variables yields roughly 25% prefill throughput improvement for free, as demonstrated by benchmarks.

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#performance

@TheAhmadOsman: Dense models like Qwen 3.8 27B are a TERRIBLE experience on unified-memory systems like DGX Spark btw DGX Sparks are be…

X AI KOLs Following · 5d ago Cached

Ahmad Osman argues that dense models like Qwen 27B perform poorly on unified-memory systems such as NVIDIA DGX Spark, suggesting MoE models are a better fit; he claims discrete GPUs like the RTX PRO 6000 deliver far better performance for agentic workloads.

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#performance

@TheAhmadOsman: By the way RTX PRO 6000 = 1.8TB/s DGX Spark = 273GB/s You should aim for higher bandwidth if agents and agentic swarms …

X AI KOLs Timeline · 5d ago Cached

A tweet highlights the large bandwidth difference between RTX PRO 6000 (1.8TB/s) and DGX Spark (273GB/s), arguing that higher bandwidth is crucial for local AI agents and agentic swarms.

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#performance

@rohanpaul_ai: Making SQLite 5% faster would already be powerful. Here, an AI agent, KISS Sorcar, got 59% improvement in under 8 hours…

X AI KOLs Following · 6d ago Cached

An AI agent called KISS Sorcar achieved a verified 1.59x geometric-mean speedup on SQLite across four benchmarks in under 8 hours for less than $150, passing over 1 million SQLite tests. This highlights the growing capability of coding agents.

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#performance

@TheAhmadOsman: Some numbers from running DeepSeek V4 Flash 0731 on a DGX Station

X AI KOLs Timeline · 6d ago Cached

Ahmad Osman shares performance numbers from running DeepSeek V4 Flash 0731 on an NVIDIA DGX Station.

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#performance

I got tired of my 300GB model loads taking 5min on RPC. PR 26291 speeds it 300% to 1min30sec (4060ti+ddr4) + (4060ti+ddr5)

Reddit r/LocalLLaMA · 6d ago

A llama.cpp/GGML PR (26291) speeds up RPC-based 300GB model loads by ~300%, cutting load time from ~5 minutes to ~1.5 minutes on consumer hardware with the GGML_RPC_LOAD_THREADS setting.

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#performance

Qwen 3.6 27B flags/settings in llama.cpp

Reddit r/LocalLLaMA · 6d ago

A user shares their llama.cpp server configuration for running Qwen 3.6 27B on an RTX 5090, achieving 80-100 t/s, and asks the community for alternative settings and tips.

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#performance

Concurrency vs. Throughput: why more parallelism can make databases slower

Lobsters Hottest · 6d ago Cached

A PlanetScale engineering post analyzes a MySQL outage caused by a long-running transaction and high concurrency, explaining how parallelism can degrade throughput and how Vitess's transaction pool handled (and amplified) the issue.

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#performance

Assembly Hall of Shame

Hacker News Top · 6d ago Cached

The Assembly Hall of Shame is a GitHub project that ranks the slowest possible single x86 instructions by exploiting hardware quirks such as MMIO latency and microcode assists, achieving extreme latencies like a 62-second fxrstor64.

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#performance

PS3 emulation is fast on ARM now

Lobsters Hottest · 6d ago Cached

RPCS3's ARM port now runs 60% faster and draws 25% less power after fixing a busy-wait timer bug, replacing x86 pause with ARM ISB, and reworking LLVM code generation. The gains come from low-level ARM optimizations driven by a cheap Android handheld test device.

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#performance

llama.cpp PR reports up to 169% faster quantized-KV decode at 118K context on Intel Battlemage from one SYCL kernel switch

Reddit r/LocalLLaMA · 6d ago

A llama.cpp PR proposes switching quantized-KV decode from the VEC to TILE SYCL kernel on Intel Battlemage, reportedly delivering up to ~169% faster decode at 118K context. The PR is open with caveats and limited independent verification.

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#performance

@rauchg: Next.js is the Next.js for SPAs

X AI KOLs Timeline · 6d ago Cached

Guillermo Rauch quips that Next.js is the Next.js for SPAs, highlighting that Next.js 16.3 makes navigations roughly 3.5× faster in v0, with an agent-driven optimization loop.

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#performance

Software Understanding in the Sciences is Really Uneven

Lobsters Hottest · 6d ago Cached

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.

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#performance

A llama.cpp PR makes Q2_0 3.0–3.6x faster on x86 CPUs, 8B decode goes 2.39 → 8.20 tok/s

Reddit r/LocalLLaMA · 2026-08-07

A llama.cpp pull request adds an x86 VNNI implementation for Q2_0 × Q8_0 dot products, delivering 3.0–3.6x CPU-only speedups on Bonsai models with bit-for-bit kernel correctness and 99.2% token agreement.

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#performance

Making Postgres 300x faster for analytics: batching, operator fusion, and SIMD

Hacker News Top · 2026-08-07 Cached

pgrust 0.2 rebuilds the Postgres query engine with batching, operator fusion, and SIMD, achieving 300x faster analytical queries and 30% faster OLTP than Postgres.

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#performance

@sashimikun_void: Prime-Bun: https://github.com/sng-asyncfunc/prime-bun… An ultra-fast Prime Agent fork designed to orchestrate concurren…

X AI KOLs Following · 2026-08-07 Cached

Prime Bun is a Bun-native fork of Prime Agent that replaces the Python notebook with a JavaScript/TypeScript runtime, dramatically reducing latency for long-running coding tasks.

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