Memory Systems in Dataflow Architectures

Compilation for Dataflow is an IBM course on Coursera about the compiler stages a PyTorch model passes through before running on an accelerator. It covers how compiler decisions affect execution, including graph breaks, synchronization caused by Python scalar reads, and the resulting loss of compiler optimization in compiled workloads.

Cerebras Systems (branded Cerebras) is a company that designs AI‑optimized compute hardware and software for large‑scale model training and inference. Its products include the Wafer‑Scale Engine (WSE) and CS‑class systems, which provide high‑performance, large‑memory accelerators for deep learning workloads.

Hy Memory is a cognitive memory engine and Python SDK from Tencent Hunyuan for LLM agents. It routes data into three task-specific memory scenes: hierarchical long-term memory for chat, two-layer session-fact and reusable-experience memory for productivity work, and the same two layers plus a version-evolution diff chain for coding tasks. The chat pipeline organizes conversations into layers including raw dialogue, atomic facts, summaries, schemas, and prospective intentions. Working and coding pipelines extract what a session did separately from lessons that may be reused; the coding pipeline also attaches the actual diffs and user-described revisions for the code touched by each fact. The SDK accepts plain text or OpenAI-format messages, supports automatic scene routing, source isolation, CRUD operations, and configurable vector, graph, and metadata stores. The repository also includes MemHub, a local-first desktop and CLI product that combines conversation history and coding traces from authorized AI applications into a managed local runtime. Hy Memory is distributed under the Apache-2.0 license and can use OpenAI-compatible LLM and embedding endpoints, with ChromaDB as a default vector store and optional Qdrant, FAISS, Kuzu, Neo4j, and MySQL backends.

An online course and community (branded Switch Dimension AI) created by Rob Shocks that teaches how to build and ship products with AI. The offering combines instructional content on building AI-powered applications with access to a learner community and is hosted at switchdimension.com.

LMCache is a KV-cache management layer for AI inference systems. It stores pages of the KV cache from GPU memory in remote storage and provides an integration point for reading stored KV pages, including for security analysis and threat discovery.