misc

Author: jstac

lectures/kesten_processes.md

@@ -208,7 +208,7 @@ time `T`) corresponds to firm size distribution in (approximate) equilibrium.
 
 ```{code-cell} ipython3
 def generate_cross_section(
-        firm, M=1_000_000, T=500, s_init=1.0, seed=123
+        firm, M=500_000, T=500, s_init=1.0, seed=123
     ):
 
     μ_a, σ_a, μ_b, σ_b, μ_e, σ_e, s_bar = firm
@@ -231,14 +231,16 @@ def generate_cross_section(
     return s
 ```
 
+Let's try running the code and generating a cross-section.
+
 ```{code-cell} ipython3
 firm = Firm()
 tic()
 data = generate_cross_section(firm).block_until_ready()
 toc()
 ```
 
-Running the above function again so we can see the speed with and without compile time.
+We run the function again so we can see the speed without compile time.
 
 ```{code-cell} ipython3
 tic()
@@ -264,13 +266,14 @@ The plot produces a straight line, consistent with a Pareto tail.
 
 #### Alternative implementation with `lax.fori_loop`
 
-We did not JIT-compile the `for` loop above because
-acceleration of outer loops makes relatively little difference terms of
-compute time.
+Although we JIT-compiled some of the code above,
+we did not JIT-compile the `for` loop.
+
+Let's try squeezing out a bit more speed
+by 
 
-However, to maximize performance, let's try squeezing out a bit more speed
-by replacing the `for` loop with
-[`lax.fori_loop`](https://jax.readthedocs.io/en/latest/_autosummary/jax.lax.fori_loop.html).
+* replacing the `for` loop with [`lax.fori_loop`](https://jax.readthedocs.io/en/latest/_autosummary/jax.lax.fori_loop.html) and
+* JIT-compiling the whole function.
 
 Here a the `lax.fori_loop` version:
 
@@ -348,7 +351,7 @@ Try writing an alternative version of `generate_cross_section_lax()` where the e
 
 Does it improve the runtime?
 
-What are the pros and cons of this approach.
+What are the pros and cons of this approach?
 
 ```{exercise-end}
 ```
@@ -401,11 +404,14 @@ data = generate_cross_section_lax(firm).block_until_ready()
 toc()
 ```
 
-This method might be faster in some cases but in general the
-relative speed will depend on the size of the cross-section and the length of
+This method might or might not be faster.
+
+In general, the relative speed will depend on the size of the cross-section and the length of
 the simulation paths.
 
-Also, this method is far more memory intensive.
+However, this method is far more memory intensive.
+
+It will fail when $T$ and $M$ become sufficiently large.
 
 ```{solution-end}
-```
+```