# #memory — MDRSS hashtag feed

> Public MDRSS cards tagged #memory.
> Canonical feed: https://mdrss.com/feeds/memory

## Cards (9)

### [Memory Forensics](https://mdrss.com/security/forensics-reverse-engineering/901418/901418.md)

Comprehensive techniques for acquiring, analyzing, and extracting artifacts from memory dumps for incident response and malware analysis. Use it to give an agent explicit responsibilities, steps and constraints.

Classification: security/forensics-reverse-engineering · Feed: security · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [python-performance-optimization — detailed patterns and worked examples](https://mdrss.com/software-craft/programming-runtime/901404/901404.md)

For advanced optimization techniques including NumPy vectorization, caching, memory management, parallelization, async I/O, database optimization, and benchmarking tools, see references/advanced-patterns.md. Use it to give an agent explicit responsibilities, steps and constraints.

Classification: software-craft/programming-runtime · Feed: software-craft · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Python Performance Optimization — Advanced Reference](https://mdrss.com/software-craft/programming-runtime/901403/901403.md)

Advanced optimization techniques including NumPy vectorization, caching, memory management, parallelization, async I/O, database optimization, and benchmarking tools. Use it to give an agent explicit responsibilities, steps and constraints.

Classification: software-craft/programming-runtime · Feed: software-craft · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Memory Math](https://mdrss.com/llm-engineering/training-fine-tuning/901367/901367.md)

Last verified: 2026-07-13 — refresh when a new size-class anchor is validated or optimizer/dtype defaults change. Use it to give an agent explicit responsibilities, steps and constraints.

Classification: llm-engineering/training-fine-tuning · Feed: llm-engineering · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [langchain-architecture — detailed patterns and worked examples](https://mdrss.com/ai-agents/agent-design-and-orchestration/901344/901344.md)

langchain-architecture — detailed patterns and worked examples captures reusable agent playbook guidance for agent design & orchestration. Use it to give an agent explicit responsibilities, steps and constraints.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Spark Training Gotchas](https://mdrss.com/llm-engineering/inference-and-quantization/901284/901284.md)

DGX Spark's GB10 chip (Grace Blackwell, SM121, 128GB unified memory, aarch64) has ten recurring failure modes across launch, memory, thermals, bandwidth, and precision. Each is named G1–G10 so it can be checked by number — the numbering is load-bearing for tooling that runs these. Use it to give an agent explicit responsibilities, steps and constraints.

Classification: llm-engineering/inference-and-quantization · Feed: llm-engineering · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Spark Memory & Thermal Ops](https://mdrss.com/platforms/devops-and-infrastructure/901283/901283.md)

DGX Spark's GB10 chip has one 128GB unified memory (UMA) pool shared by CPU and GPU, and a sustained power ceiling well below its rated figure. Both break discrete-GPU assumptions: headroom isn't what nvidia-smi reports, and a run that starts fast will slow down mid-job with no. Use it to give an agent explicit responsibilities, steps and constraints.

Classification: platforms/devops-and-infrastructure · Feed: platforms · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Managed Agents — Memory Stores](https://mdrss.com/ai-agents/agent-design-and-orchestration/901141/901141.md)

Sessions are ephemeral by default — when one ends, anything the agent learned is gone. A memory store is a workspace-scoped collection of small text documents that persists across sessions. When a store is attached to a session (via resources ), it is mounted into the cont. Use it as a repeatable review, validation or hardening pass.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [TencentDB Agent Memory](https://mdrss.com/ai-agents/agent-frameworks/1102/1102.md)

· Team Play · Technical Implementation · Benchmark English · 简体中文 --- Start all three services in one go (memory-core + memory-hub + proxy): Open the panel: http://localhost:8125. Complete installation documentation (standalone Memory Hub deployment, Proxy + Claude Code / CodeBuddy usage, stop and cleanup, port reference, etc.) is available in INSTALL.md (中文: INSTALLCN.md).

Classification: ai-agents/agent-frameworks · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1