master
zeus.run.master
Defines the ZeusMaster
class, which drives batch size optimization and training.
ZeusMaster
Drives Zeus across multiple recurrences of a job.
The main purpose of ZeusMaster
is to launch training scripts integrated
with ZeusDataLoader
, controlling it by setting
environment variables. For the environment variables, see the
run_job
method as well as
ZeusDataLoader
's class docstring.
The optimal batch size is searched for and exploited using the
BatchSizeOptimizer
object passed in
through the constructor.
Source code in zeus/run/master.py
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__init__
__init__(batch_size_optimizer, log_base, monitor_path, seed=123456, observer_mode=False, profile_warmup_iters=10, profile_measure_iters=40)
Parameters:
Name | Type | Description | Default |
---|---|---|---|
batch_size_optimizer |
BatchSizeOptimizer
|
The user is expected to construct the
|
required |
log_base |
str
|
Absolute path where logs will be stored. A separate directory will be created inside, whose name is determined by the job and current time. |
required |
monitor_path |
str
|
Absolute path to the power monitor binary. |
required |
seed |
int
|
The random seed. Every invocation of the |
123456
|
observer_mode |
bool
|
When Observer Mode is on, the maximum power limit is always used instead of the optimal power limit. However, internal time and energy accounting will be done as if the cost-optimal power limit is used. |
False
|
profile_warmup_iters |
int
|
Number of iterations to warm up on a specific power limit.
This is passed to the |
10
|
profile_measure_iters |
int
|
Number of iterations to measure on a specific power limit.
This is passed to the |
40
|
Source code in zeus/run/master.py
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build_logdir
build_logdir(job, num_recurrence, eta_knob, beta_knob, exist_ok=True)
Build the ZEUS_LOG_DIR
string and create the directory.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
job |
Job
|
Job to run. |
required |
num_recurrence |
int
|
The total number of recurrences. |
required |
eta_knob |
float
|
\(\eta\) used in the cost metric. \(\textrm{cost} = \eta \cdot \textrm{ETA} + (1 - \eta) \cdot \textrm{MaxPower} \cdot \textrm{TTA}\) |
required |
beta_knob |
float
|
|
required |
exist_ok |
bool
|
Passed to |
True
|
Source code in zeus/run/master.py
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run_job
run_job(job, batch_size, learning_rate, seed, logdir, rec_i, tries, eta_knob, cost_ub)
Launch the training job.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
job |
Job
|
The job to run. |
required |
batch_size |
int
|
The batch size to use. |
required |
learning_rate |
float
|
The learning rate to use, scaled based on |
required |
seed |
int
|
The random seed to use for training. |
required |
logdir |
str
|
Directory to store log files in. |
required |
rec_i |
int
|
Recurrence number of this run of the job. |
required |
tries |
int
|
Retry number of this recurrence of the job. |
required |
eta_knob |
float
|
\(\eta\) used in the cost metric. \(\textrm{cost} = \eta \cdot \textrm{ETA} + (1 - \eta) \cdot \textrm{MaxPower} \cdot \textrm{TTA}\) |
required |
cost_ub |
float
|
Cost upper bound. The job is terminated when the next epoch is going to exceed the cost upper bound. |
required |
Returns:
Type | Description |
---|---|
tuple[float, float, bool]
|
A tuple of energy consumption, time consumption, and whether the job reached the target metric. |
Source code in zeus/run/master.py
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run
run(job, num_recurrence, batch_sizes, beta_knob, eta_knob)
Run a job that sequentially recurs without overlap.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
job |
Job
|
The job to run. |
required |
num_recurrence |
int
|
How many times the job recurs. |
required |
batch_sizes |
list[int]
|
List of feasible batch sizes. |
required |
beta_knob |
float
|
|
required |
eta_knob |
float
|
\(\eta\) used in the cost metric. \(\textrm{cost} = \eta \cdot \textrm{ETA} + (1 - \eta) \cdot \textrm{MaxPower} \cdot \textrm{TTA}\) |
required |
Returns:
Type | Description |
---|---|
list[HistoryEntry]
|
A list of |
Source code in zeus/run/master.py
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