fn init() -> Result<(), GpuError>
Source: gpu/lib.joule:28
fn list_devices() -> Vec<GpuDevice>
Source: gpu/lib.joule:43
fn default_device() -> Option<GpuDevice>
Source: gpu/lib.joule:60
fn most_efficient_device() -> Option<GpuDevice>
Source: gpu/lib.joule:74
struct GpuEnergyResult
Source: gpu/lib.joule:103
fn launch(
Source: gpu/lib.joule:136
fn launch_on_queue(
Source: gpu/lib.joule:180
struct GpuEnergyMonitor
Continuous GPU energy monitor that samples power in the background. Start the monitor before a sequence of GPU operations, then stop it to get an aggregate energy report covering the entire span.
Source: gpu/lib.joule:225
fn start(device: &GpuDevice, interval: std::time::Duration) -> Self
Source: gpu/lib.joule:243
fn stop(&mut self) -> GpuEnergyReport
Stop monitoring and return an aggregate energy report.
Source: gpu/lib.joule:273
fn drop(&mut self)
Source: gpu/lib.joule:330
struct GpuEnergyReport
Source: gpu/lib.joule:340
fn estimated_co2_kg(&self, carbon_intensity_kg_per_kwh: f64) -> f64
Estimated CO2 emissions in kilograms. Uses the given carbon intensity (kg CO2 / kWh). Global average is ~0.5.
Source: gpu/lib.joule:358
fn print(&self)
Print a human-readable summary.
Source: gpu/lib.joule:364
fn sample_device_power(kernel: &GpuKernel) -> Option<f64>
Sample power from the device using backend-specific management APIs. Returns watts if available.
Source: gpu/lib.joule:385
fn read_device_power(device: &GpuDevice) -> Option<f64>
Read power from a device handle using the appropriate management library.
Source: gpu/lib.joule:391
fn estimate_idle_power(device: &GpuDevice) -> f64
Estimate idle power for a device based on its backend and capabilities.
Source: gpu/lib.joule:415
fn compute_energy(
Compute energy from timing and optional power readings. Returns (energy_joules, avg_power_watts, peak_power_watts).
Source: gpu/lib.joule:426
enum GpuError
Source: gpu/lib.joule:463
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result
Source: gpu/lib.joule:489
fn launch_with_budget(
Source: gpu/lib.joule:524
fn device_power_profile(device: &GpuDevice) -> (f64, f64, f64)
Convenience: get a device's backend-specific energy cost model parameters. Returns (estimated_idle_watts, estimated_active_watts, estimated_peak_watts).
Source: gpu/lib.joule:551