DeepSeek Elastic Compute (DSec)

# Computer Science > Distributed, Parallel, and Cluster Computing [Submitted on 19 Sep 2026] # Title:DeepSeek Elastic Compute (DSec): A Sandbox Infrastructure for Effective Agentic Training at Scale View PDF HTML (experimental) Abstract:Large-scale agentic training and evaluation with large language models (LLMs) rely on isolated, stateful execution environments in which models inspect repositories, invoke tools, execute commands, and interact with task-specific services. These workloads create sandboxes in large bursts, span heterogeneous functionality and isolation…

Research · AI · Machine Learning · Research · Infrastructure

Mercury 2.5: Intelligence, Performance and Price Analysis

Artificial Analysis profiles Inception's Mercury 2.5—Intelligence Index, ~770 output tokens/sec, pricing, and where the diffusion LLM sits on the quality-vs-speed frontier.

Research · AI · LLMs · Benchmarks · Performance

Training a 4B model to produce 81% faster query plans than Postgres

Leis et al. asked this exact question in 2015. Then, they asked it again 10 years later. Despite an enormous body of research spanning a decade since their original exploration, they found that query optimizers continue to leave much to be desired. I was surprised when I first learned about this. A Postgres database should know everything about the stuff that lives in its tables, no? How hard can it be?

Research · AI · Machine Learning · Performance · Databases

RTK reports huge token savings, but our cost benchmarks disagree

Quesma ran RTK (Rust Token Killer) against Terminal-Bench 2.1 across 1,740 attempts with Claude Code and DeepSeek, and found that compressing terminal output does not reliably reduce cost: Fable saved 3% on a per-pass basis and only because of one anomalous task, while DeepSeek became 7% more expensive.

Research · AI Coding Agents · LLMs · Benchmarks · Cost Optimization

Getting 50 GB/s Back Out of the ANE

Eileen Yoon identifies an RTL performance bug in the Apple M3 Neural Engine where DRAM throughput collapses from 45–60 GB/s to 17–19 GB/s whenever total weight size is an exact multiple of 1 MiB. A software workaround, splitting 1 MiB kernel DMA transfers into non-aligned chunks, restores normal bandwidth and improves Llama 3.2 1B token throughput from 10 to 24 tokens per second.

Research · Apple Silicon · Neural Engine · Performance · Hardware

Semantics for 2D Rasterization

Kulkarni, Whiting, and Panchekha introduce μSkia—a Lean-mechanized formal semantics for Skia 2D graphics—and an optimizer that speeds rasterization ~18.7% on Chrome-derived Skia programs while proving replacements correct.

Research · Research · Performance · Programming · Hardware

Cache-to-Cache: Direct Semantic Communication Between Large Language Models

Fu et al. propose Cache-to-Cache (C2C): multi-LLM systems exchange KV-cache semantics directly instead of text tokens, aiming for richer inter-model communication with lower latency and token cost.

Research · LLMs · Research · Machine Learning · AI