arXiv (All)
open access
Divide and conquer: Scalable performance and energy in MCM GPUs
Multi-chip-module (MCM) GPUs offer a promising path to scale compute capability beyond monolithic designs by integrating multiple chiplets on a common package. However, the impact of disaggregation on performance scalability and energy consumption remains underexplored. The design space grows rapidl
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- GPUBreach: Privilege Escalation Attacks on GPUs using Rowhammer#1110228
- WarpGuard: Towards Control-Flow Attestation for Heterogeneous CPU-GPU Execution#370276
- AMDKernelVault: Large-Scale Datasets and Agentic Training for AMD GPU Kernel Optimization#1069969
- KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation#1117786
- GPUHammer: Rowhammer Attacks on GPU Memories are Practical#1011000
Record · ID 1187739
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive