diff options
| -rwxr-xr-x | lib/dfatool.py | 67 |
1 files changed, 60 insertions, 7 deletions
diff --git a/lib/dfatool.py b/lib/dfatool.py index 995508e..7eb7359 100755 --- a/lib/dfatool.py +++ b/lib/dfatool.py @@ -485,7 +485,7 @@ class ParamStats: class TimingData: """ - Loader for timing model traces measured with on-board timers using ``harness.OnboardTimerHarness``. + Loader for timing model traces measured with on-board timers using `harness.OnboardTimerHarness`. Excpets a specific trace format and UART log output (as produced by generate-dfa-benchmark.py). Prunes states from output. (TODO) @@ -578,7 +578,18 @@ class RawData: """ Create a new RawData object. - Each filename element corresponds to a measurement run. + Each filename element corresponds to a measurement run. It must be a tar archive with the following contents: + + * `setup.json`: measurement setup. Must contain the keys `state_duration` (how long each state is active, in ms), + `mimosa_voltage` (voltage applied to dut, in V), and `mimosa_shunt` (shunt value, in Ohm) + * `src/apps/DriverEval/DriverLog.json`: PTA traces and parameters for this benchmark. + Layout: List of traces, each trace has an 'id' (numeric, starting with 1) and 'trace' (list of states and transitions) element. + Each trace has an even number of elements, starting with the first state (usually `UNINITIALIZED`) and ending with a transition. + Each state/transition must have the members `.parameter` (parameter values, empty string or None if unknown), `.isa` ("state" or "transition") and `.name`. + Each transition must additionally contain `.plan.level` ("user" or "epilogue"). + Example: `[ {"id": 1, "trace": [ {"parameter": {...}, "isa": "state", "name": "UNINITIALIZED"}, ...] }, ... ] + * At least one `*.mim` file. Each file corresponds to a single execution of the entire benchmark (i.e., all runs described in DriverLog.json) and starts with a MIMOSA Autocal calibration sequence. + MIMOSA files are parsed by the `MIMOSA` class. """ self.filenames = filenames.copy() self.traces_by_fileno = [] @@ -760,8 +771,53 @@ class RawData: """ Return a list of DFA traces annotated with energy, timing, and parameter data. - Suitable for the PTAModel constructor. - See PTAModel(...) docstring for format details. + Each DFA trace contains the following elements: + * `id`: Numeric ID, starting with 1 + * `total_energy`: Total amount of energy (as measured by MIMOSA) in the entire trace + * `orig_id`: Original trace ID. May differ when concatenating multiple (different) benchmarks into one analysis, i.e., when calling RawData() with more than one file argument. + * `trace`: List of the individual states and transitions in this trace. Always contains an even number of elements, staring with the first state (typically "UNINITIALIZED") and ending with a transition. + + Each trace element (that is, an entry of the `trace` list mentioned above) contains the following elements: + * `isa`: "state" or "transition" + * `name`: name + * `offline`: List of offline measumerents for this state/transition. Each entry contains a result for this state/transition during one benchmark execution. + Entry contents: + - `clip_rate`: rate of clipped energy measurements, 0 .. 1 + - `raw_mean`: mean raw MIMOSA value + - `raw_std`: standard deviation of raw MIMOSA value + - `uW_mean`: mean power draw, uW + - `uw_std`: standard deviation of power draw, uW + - `us`: state/transition duration, us + - `uW_mean_delta_prev`: (only for transitions) difference between uW_mean of this transition and uW_mean of previous state + - `uW_mean_elta_next`: (only for transitions) difference between uW_mean of this transition and uW_mean of next state + - `timeout`: (only for transitions) duration of previous state, us + * `offline_aggregates`: Aggregate of `offline` entries. dict of lists, each list entry has the same length + - `duration`: state/transition durations ("us"), us + - `energy`: state/transition energy ("us * uW_mean"), us + - `power`: mean power draw ("uW_mean"), uW + - `power_std`: standard deviations of power draw ("uW_std"), uW^2 + - `paramkeys`: List of lists, each sub-list contains the parameter names corresponding to the `param` entries + - `param`: List of lists, each sub-list contains the parameter values for this measurement. Typically, all sub-lists are the same. + - `rel_energy_prev`: (only for transitions) transition energy relative to previous state mean power, pJ + - `rel_energy_next`: (only for transitions) transition energy relative to next state mean power, pJ + - `timeout`: (only for transitions) duration of previous state, us + * `offline_attributes`: List containing the keys of `offline_aggregates` which are meant to be part of themodel. + This list ultimately decides which hardware/software attributes the model describes. + If isa == state, it contains power, duration, energy + If isa == transition, it contains power, duration, energy, rel_energy_prev, rel_energy_next, timeout + * `online`: List of online estimations for this state/transition. Each entry contains a result for this state/transition during one benchmark execution. + Entry contents for isa == state: + - `time`: state/transition + Entry contents for isa == transition: + - `timeout`: Duration of previous state, measured using on-board timers + * `parameter`: dictionary describing parameter values for this state/transition. Parameter values refer to the begin of the state/transition and do not account for changes made by the transition. + * `plan`: Dictionary describing expected behaviour according to schedule / offline model. + Contents for isa == state: `energy`, `power`, `time` + Contents for isa == transition: `energy`, `timeout`, `level`. + If level is "user", the transition is part of the regular driver API. If level is "epilogue", it is an interrupt service routine and not called explicitly. + Each transition also contains: + * `args`: List of arguments the corresponding function call was called with. args entries are strings which are not necessarily numeric + * `code`: List of function name (first entry) and arguments (remaining entries) of the corresponding function call """ self.verbose = verbose if self.preprocessed: @@ -945,9 +1001,6 @@ class AnalyticModel: Supports both static and parameter-based model attributes, and automatic detection of parameter-dependence. - The model heavily relies on two internal data structures: - PTAModel.by_name and PTAModel.by_param. - These provide measurements aggregated by (function/state/...) name and (for by_param) parameter values. Layout: dictionary with one key per name ('send', 'TX', ...) or |