Hardware on Joulie

CPU Support and Power Capping

Mon, 01 Jan 0001 00:00:00 +0000

Joulie supports node-level CPU power capping through NodeTwin intents enforced by the agent.

Contract model

CPU intent is defined in NodeTwin.spec.cpu:

packagePowerCapWatts (optional absolute cap)
packagePowerCapPctOfMax (optional normalized profile intent)

Precedence:

packagePowerCapWatts if present
otherwise packagePowerCapPctOfMax

Policy behavior

Operator profile assignment remains performance vs eco. CPU cap values are generated per profile and written into NodeTwin.spec:

performance profile typically maps to a higher cap (often 100%)
eco profile maps to a lower cap

For heterogeneous nodes, percentage-based intent remains useful because each node resolves normalized intent using node-local capabilities. If percentage intent cannot be converted to watts (for example missing RAPL range), the agent applies a DVFS percent fallback path when possible.

GPU Support (NVIDIA + AMD)

Mon, 01 Jan 0001 00:00:00 +0000

Joulie supports node-level GPU power-cap intents for NVIDIA and AMD.

Validation status

GPU support has been validated in simulator mode only (no bare-metal GPU access yet). The host code paths are designed to work on bare metal (NVIDIA + AMD) when GPU nodes are available.

Contract model

NodeTwin.spec.gpu.powerCap defines a per-GPU cap intent:

scope: perGpu
capWattsPerGpu (absolute, optional)
capPctOfMax (percentage, optional)

Precedence:

capWattsPerGpu if present
otherwise capPctOfMax

The same cap is applied uniformly to all GPUs on the node.

Hardware Modeling and Physical Power Model

Mon, 01 Jan 0001 00:00:00 +0000

This page documents how Joulie models CPUs and GPUs across the project using a mix of:

official vendor specifications and management APIs,
public measured power curves, and
explicit proxy models where public exact curves are not yet available.

It serves two closely related purposes:

for the agent, it describes the hardware assumptions used to resolve caps, interpret device limits, and reason about how throttling affects attainable performance
for the simulator, it describes the physical model used to turn utilization and control actions into simulated power and slowdown

Quick summary

If you want the short version before the details: