def reference_waveform(adp, waveform):
program = DSProgDB.get_prog(adp.metadata[ADPMetadata.Keys.DSNAME])
dssim = DSProgDB.get_sim(program.name)
dsinfo = DSProgDB.get_info(program.name)
ref_waveforms = get_reference_waveforms(program, dssim)
reference = ref_waveforms[waveform.variable]
return program, dsinfo, dssim, reference
def print_summary(dev, adp, rmse):
program = DSProgDB.get_prog(adp.metadata[ADPMetadata.Keys.DSNAME])
dssim = DSProgDB.get_sim(program.name)
dsinfo = DSProgDB.get_info(program.name)
runtime = dev.time_constant / adp.tau * dssim.sim_time
bandwidth = (1.0 / dev.time_constant) * adp.tau
power = energymodel.compute_power(adp, bandwidth)
energy = runtime * power
print("-------- general -------------")
print("runtime = %f ms" % (runtime * 1000))
print("power = %f mW" % (power * 1e3))
print("energy = %f uJ" % (energy * 1e6))
print("quality = %f %%" % rmse)
print("------------ metadata ----------------")
print(adp.metadata)
print("------------ lgraph ----------------")
by_block = {'fanout':[],'adc':[],'dac':[],'mult':[], 'integ':[], \
'extout':[],'extin':[],'cin':[],'cout':[],'tin':[],'tout':[]}
total_blocks = 0
for cfg in adp.configs:
if cfg.inst.block in by_block:
by_block[cfg.inst.block].append(cfg.mode)
total_blocks += 1
total_conns = len(list(adp.conns))
for block_name, modes in by_block.items():
if len(modes) > 0:
print("%s = %d modes=%s" % (block_name, len(modes), set(modes)))
print("total blocks = %d" % total_blocks)
print("total conns = %d" % total_conns)
print("------------ lscale ----------------")
scale_factors = []
injected_vars = []
for cfg in adp.configs:
for stmt in cfg.stmts:
if stmt.type == adplib.ConfigStmtType.CONSTANT:
scale_factors.append(stmt.scf)
if stmt.type == adplib.ConfigStmtType.PORT:
scale_factors.append(stmt.scf)
if stmt.type == adplib.ConfigStmtType.EXPR:
for scf in stmt.scfs:
scale_factors.append(scf)
for inj in stmt.injs:
injected_vars.append(inj)
print("tau=%f" % (adp.tau))
print("scf total = %d" % len(scale_factors))
print("scf uniq = %d" % len(set(scale_factors)))
print("inj total = %d" % len(injected_vars))
print("inj uniq = %d" % len(set(injected_vars)))
def plot_preamble_realtime(entry):
# compute reference using information from first element
output = list(entry.outputs())[0]
palette = sns.color_palette()
ax = plt.subplot(1, 1, 1)
info = DSProgDB.get_info(entry.program)
title = info.name
ax.set_xlabel('time (ms)', fontsize=18)
ax.tick_params(labelsize=16)
ax.set_ylabel(info.units, fontsize=18)
#ax.set_xticklabels([])
#ax.set_yticklabels([])
#ax.set_title(title,fontsize=20)
ax.grid(False)
return ax
def visualize(db):
header = [
'description', 'observation', 'time', 'diffeqs', 'funcs', 'nonlinear'
]
desc = 'dynamical system benchmarks used in evaluation. $\dagger$ these benchmarks '
table = common.Table('Benchmarks', desc, 'bmarksumm', '|c|lccccc|')
table.two_column = True
bool_to_field = {True: 'yes', False: 'no'}
table.set_fields(header)
table.horiz_rule()
table.header()
table.horiz_rule()
for bmark in table.benchmarks():
bmark_name = bmark
if 'heat1d' in bmark:
bmark_name = 'heat1d'
if not DSProgDB.has_prog(bmark):
print("skipping %s... no info" % bmark)
continue
info = DSProgDB.get_info(bmark)
prog = DSProgDB.get_prog(bmark)
dssim = DSProgDB.get_sim(bmark)
n_diffeqs = 0
n_funcs = 0
for v, bnd in prog.bindings():
if bnd.op == op.OpType.INTEG:
n_diffeqs += 1
else:
n_funcs += 1
print(info)
entry = {
'description': info.description,
'observation': info.observation,
'diffeqs': n_diffeqs,
'funcs': n_funcs,
'time': str(dssim.sim_time) + " su",
'nonlinear': bool_to_field[info.nonlinear]
}
table.data(bmark, entry)
table.horiz_rule()
table.write(common.get_path('bmarks.tbl'))
def plot_preamble(entry, TREF, YREF):
# compute reference using information from first element
output = list(entry.outputs())[0]
palette = sns.color_palette()
ax = plt.subplot(1, 1, 1)
info = DSProgDB.get_info(entry.program)
title = info.name
ax.set_xlabel('simulation time', fontsize=32)
ax.set_ylabel(info.units, fontsize=32)
ax.set_xticklabels([])
ax.set_yticklabels([])
#ax.set_title(title,fontsize=20)
ax.set_xlim((min(TREF), max(TREF)))
margin = (max(YREF) - min(YREF)) * 0.1
lb = min(YREF) - margin
ub = max(YREF) + margin
ax.set_ylim((lb, ub))
ax.grid(False)
ax.plot(TREF,YREF,label='reference',
linestyle='-', \
linewidth=3, \
color="#E74C3C")
return ax