#
# jaxpi.py
# Neil Gershenfeld 12/21/24
# Jax pi calculation benchmark
# pi = 3.14159265358979323846
#
import jax
import jax.numpy as jnp
import numpy as np
import time
#
NPTS = 100000000
#
a = 0.5
b = 0.75
c = 0.25
#
# alternate compilation values to prevent caching
#
a0 = 0.6
b0 = 0.7
c0 = 0.2
#
print("\nNumPy version:")
def num_calcpi(a,b,c):
   i = np.arange(1,(NPTS+1),dtype=float)
   pi = np.sum(a/((i-b)*(i-c)))
   return pi
start_time = time.time()
pi = num_calcpi(a,b,c)
end_time = time.time()
mflops = NPTS*5.0/(1.0e6*(end_time-start_time))
print("NPTS = %d, pi = %f"%(NPTS,pi))
print("time = %f, estimated MFlops = %f"%(end_time-start_time,mflops))
#
print("\ncompile Jax version:")
def jax_calcpi(a,b,c):
   i = jnp.arange(1,(NPTS+1),dtype=float)
   pi = jnp.sum(a/((i-b)*(i-c)))
   return pi
start_time = time.time()
pi = jax_calcpi(a0,b0,c0).block_until_ready()
end_time = time.time()
print("time = %f"%(end_time-start_time))
#
print("\nrun Jax version:")
start_time = time.time()
pi = jax_calcpi(a,b,c).block_until_ready()
end_time = time.time()
mflops = NPTS*5.0/(1.0e6*(end_time-start_time))
print("NPTS = %d, pi = %f"%(NPTS,pi))
print("time = %f, estimated MFlops = %f"%(end_time-start_time,mflops))
#
print("\ncompile Jax Jit version:")
jax_jit_calcpi = jax.jit(jax_calcpi)
start_time = time.time()
pi = jax_jit_calcpi(a0,b0,c0).block_until_ready()
end_time = time.time()
print("time = %f"%(end_time-start_time))
#
print("\nrun Jax Jit version:")
start_time = time.time()
pi = jax_jit_calcpi(a,b,c).block_until_ready()
end_time = time.time()
mflops = NPTS*5.0/(1.0e6*(end_time-start_time))
print("NPTS = %d, pi = %f"%(NPTS,pi))
print("time = %f, estimated MFlops = %f"%(end_time-start_time,mflops))