ram-coffers
LLM infrastructure cost reduction via NUMA-aware weight banking: 147 t/s (8.8x stock llama.cpp) on refurbished enterprise POWER8. Self-hosted inference, no cloud APIs. Part of the Proof of Physical AI stack.
File Explorer
- bug_report.md
- feature_request.md
- build.yml
- ci.yml
- rtc-reward.yml
- CODEOWNERS
- dependabot.yml
- ram_coffers_topology.cpython-312.pyc
- aes-entropy-collapse.h
- apple-pse-config.h
- apple-pse-integration.h
- architecture-general-pse.pdf
- bench-pse-apple.c
- BRIEFING-sparse-metal-matmul.md
- EQUATION.md
- HANDOFF-gpu-native-collapse.md
- llama-cpp-patch.md
- Makefile
- neon-collapse.h
- PAPER-architecture-general-pse.md
- pse-gather-collapse.metal
- pse-matmul-collapse.h
- pse-minimal.h
- pse-sparse-attention.metal
- pse-sparse-ffn.metal
- pse-unified-sparse-ffn.h
- README.md
- RESULTS-M2-2026-07-09.md
- RESULTS-M2-METAL-TIER1-2026-07-11.md
- setup-mac-m2.sh
- SPARSE_ATTENTION_PATCH.md
- unified-memory-coffers.h
- BENCHMARK_REPORT.md
- BLOG_RAM_COFFERS_VS_DEEPSEEK.md
- README_HARNESS.md
- BENCHMARK_RECIPE.md
- FALLBACK_BEHAVIOR.md
- PPA_INTEGRATION.md
- G9XC.md
- GEN9_SPLITTING.md
- REFERENCES.md
- __init__.py
- __main__.py
- backends.py
- cli.py
- coordinator.py
- dedup.py
- dispatch.py
- errors.py
- fp8.py
- hardware.py
- inventory.py
- model.py
- node.py
- planner.py
- protocol.py
- transport.py
- expert.comp
- expert_avx2.c
- expert_hip.hip
- fp8.c
- fp8.h
- kernel_test.c
- Makefile
- __init__.py
- test_backends.py
- test_dedup.py
- test_dispatch.py
- test_fp8.py
- test_hardware.py
- test_inventory.py
- test_model.py
- test_planner.py
- test_protocol.py
- test_transport.py
- .gitignore
- README.md
- emotional_attractor_test.py
- modern_hopfield_layer.py
- neuromorphic_benchmark_suite.py
- neuromorphic_prompt_translator.py
- grail_v_paper.tex
- GRAIL_V_PAPER_FINAL.md
- ABLATION_SUMMARY.md
- ANIMATEDIFF_ANALYSIS.md
- ATTRACTOR_ANALYSIS_RESULTS.txt
- README.md
- SVD_BASELINE_ANALYSIS.md
- test_ram_coffers_topology.cpython-312-pytest-9.1.0.pyc
- test_ram_coffers_topology.py
- aes-collapse.h
- bench-aes-collapse.c
- Makefile
- README.md
- .gitignore
- BCOS.md
- bench_vcipher_collapse.c
- BENCHMARK.md
- benchmark_coffers_vs_llamacpp.sh
- benchmark_harness.sh
- CHANGELOG.md
- CODE_OF_CONDUCT.md
- COMMERCIAL.md
- CONTRIBUTING.md
- DEEPSEEK_COMPARISON.md
- FALLBACK_BEHAVIOR.md
- FAQ.md
- ggml-coffer-mmap.h
- ggml-intelligent-collapse.h
- ggml-neuromorphic-coffers.h
- ggml-pse-integration.h
- ggml-ram-coffer.h
- ggml-ram-coffers.h
- ggml-symbolic-neural-bridge.h
- ggml-topk-collapse-vsx.h
- ggml-vcipher-collapse.h
- LICENSE
- llms.txt
- NOTICE
- power8-compat.h
- PR_BODY.md
- PRIORITY_CLAIM.md
- pse-entropy-burst.h
- QUICK_START.md
- ram_coffers_topology.py
- README.md
- SECURITY.md
- vcipher-flash-attn-patch.c
- youtube-evidence-dec17-2025.png
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Command Glossary
Commands referenced in this DOCs, explained below.
cmake
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cmake
Cross-platform build automation system, that generates recipes for native build systems.
cmake {{path/to/project_directory}}
Generate a build recipe in the current directory with `CMakeLists.txt` from a project directory:
cmake --build {{path/to/build_directory}}
Use a generated recipe in a given directory to build artifacts:
cmake --install {{path/to/build_directory}} --strip
Install the build artifacts into `/usr/local/` and strip debugging symbols:
python3
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python3
This command is an alias of `python`.
tldr python
View documentation for the original command:
lscpu
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lscpu
Display information about the CPU architecture.
lscpu
Display information about all CPUs:
lscpu {{[-e|--extended]}}
Display information in a table:
lscpu {{[-e|--extended]}} {{[-b|--online]}}
Display only information about online CPUs in a table:
numactl
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numactl
Control NUMA policy for processes or shared memory.
numactl --cpunodebind={{0}} --membind={{0,1}} -- {{command}} {{command_arguments}}
Run a command on node 0 with memory allocated on node 0 and 1:
numactl --physcpubind={{+0-4,8-12}} -- {{command}} {{command_arguments}}
Run a command on CPUs (cores) 0-4 and 8-12 of the current cpuset:
numactl --interleave={{all}} -- {{command}} {{command_arguments}}
Run a command with its memory interleaved on all CPUs:
