modified the README.md to update with 1.8, removed deprecated ParallelIterators notebook, added a new notebook as part of remote functions

Signed-off-by: Jules S.Damji <jules@anyscale.com>

Author: Jules S.Damji

README.md

@@ -6,11 +6,11 @@ core features for distributed patterns.
 These examples have been tested in the following environments:
 
   - Ubuntu 18.04 LTS
-  - macOS 10.15
+  - macOS 11.6, Big Sur
 
 Using:
 
-  - Ray versions 1.2, 1.3, 1.4 (not the early release candidates)
+  - Ray versions 1.7+ (not the early release candidates)
   - Python versions: 3.6, 3.7, 3.8
 
 Currently, Python **3.9** is not supported by Ray.
@@ -70,9 +70,10 @@ Browse to <http://localhost:8888/lab> to continue.
 tour through the core features of Ray, which provide powerful yet
 easy-to-use design patterns for implementing distributed systems in
 Python. This training includes a brief talk to provide overview of
-concepts, then coding for remote functions, actors, parallel
-iterators, and so on. Then we'll follow with Q&A. All code is
-available in notebooks in the GitHub repo.
+concepts, then coding for remote functions, tasks, object references and 
+resolutions, actors, and so on. 
+
+Then we'll follow with Q&A. All code is available in notebooks in the GitHub repo.
 
 ### Intended Audience
 
@@ -99,11 +100,11 @@ level components in Ray, such as RLlib and Ray Tune.
   3. Background, primary sources, and closely related resources about distributed systems
   4. Code samples:
 		* Remote Functions: [`ex_01_remo_func.ipynb`](https://github.com/DerwenAI/ray_tutorial/blob/main/ex_01_remo_func.ipynb)
+		* Remote Functions: [`ex_02_remo_func.ipynb`](https://github.com/DerwenAI/ray_tutorial/blob/main/ex_02_remo_func.ipynb)
 		* Remote Objects: [`ex_02_remo_objs.ipynb`](https://github.com/DerwenAI/ray_tutorial/blob/main/ex_02_remo_objs.ipynb)
 		* Remote Methods: [`ex_03_remo_meth.ipynb`](https://github.com/DerwenAI/ray_tutorial/blob/main/ex_03_remo_meth.ipynb)
 		* Multiprocessing Pool: [`ex_04_mult_pool.ipynb`](https://github.com/DerwenAI/ray_tutorial/blob/main/ex_04_mult_pool.ipynb)
 		* JobLib: [`ex_05_job_lib.ipynb`](https://github.com/DerwenAI/ray_tutorial/blob/main/ex_05_job_lib.ipynb)
-		* Parallel Iterators: [`ex_06_para_iter.ipynb`](https://github.com/DerwenAI/ray_tutorial/blob/main/ex_06_para_iter.ipynb)
    5. Profiling: comparing trade-offs and overhead
 		* Estimate Pi: [`pi.ipynb`](https://github.com/DerwenAI/ray_tutorial/blob/main/pi.ipynb)
    6. Ray Summit, Anyscale Connect, developer forums, and other resources

dat/file_1.txt

@@ -0,0 +1,10 @@
+  0, 48, 72, 75, 54, 89, 84, 68,  9, 38
+  3, 40, 73, 58, 10, 35, 96,  6, 65, 33
+ 55, 67, 12, 97, 52, 73,  7, 76, 39, 50
+ 59, 34, 20, 40, 92, 55, 11, 39, 93, 38
+ 89, 89, 37, 52, 48, 86, 49,  3, 19, 50
+ 84, 37, 68, 11, 20, 36, 46, 61, 52, 77
+ 70, 90, 56, 55, 49, 76, 94, 28, 32, 23
+  5, 44, 92, 15, 53, 63, 87, 75, 61, 25
+ 51, 58, 29, 30, 93, 94, 52, 72, 80, 27
+  1, 28, 82, 35, 89, 36, 10, 84, 85, 65

dat/file_2.txt

@@ -0,0 +1,10 @@
+101, 31, 83,124, 41, 73,  0,121, 14, 98
+137,  3, 77, 38,117, 79,104, 96, 62,117
+ 99, 92,139, 29, 59, 30,116, 30, 74, 12
+130,105,145,124, 39, 50, 66,  9,126, 24
+ 32, 33, 34, 90, 43,140,136,149,140, 22
+ 14,  8,138,101,136, 60, 41,110, 92,105
+ 44, 76,104,  6,121,135, 41,132,131, 26
+  1,  1,112, 45,146, 29, 44,104, 75,122
+132, 63, 70,109, 49, 75, 33, 36, 38,105
+131, 71, 51, 79,109,146, 71, 27, 65,126

ex_01_remo_func.ipynb

@@ -23,7 +23,10 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "First, let's start Ray…"
+    "First, let's start Ray… \n",
+    "\n",
+    "This will start Ray on the local host, with headnode and workers for each core or CPU available.\n",
+    "You can check the resources being used."
    ]
   },
   {
@@ -38,7 +41,15 @@
     "ray.init(\n",
     "    ignore_reinit_error=True,              # Don't print error messages if a Ray instance is already running. Attach to it\n",
     "    logging_level=logging.ERROR,           \n",
-    ")"
+    ")\n",
+    "ray.cluster_resources()                    # get the cluster resources"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Ray Dashboard accessible at URI: [http://127.0.0.1:8265](http://127.0.0.1:8265)"
    ]
   },
   {
@@ -129,7 +140,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The result can be retrieved with `ray.get`"
+    "The result can be retrieved with `ray.get`, which is a blocking call if the task is still not finished"
    ]
   },
   {
@@ -147,7 +158,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Invocations of Ray *remote functions* happen in parallel, and all computation gets performed in the background, driven by Ray's internal event loop.\n",
+    "Invocations of Ray *remote functions* happen in parallel, and all computation gets performed in the background, driven by Ray's internal event loop. Remote calls return immediately, with a Python Future Object reference.\n",
     "\n",
     "To illustrate this, first let's define a relatively \"slow\" function, by adding a 10 second delay..."
    ]
@@ -187,7 +198,6 @@
     "for i in range(4):\n",
     "    future = slow_function.remote()\n",
     "    futures_list.append(future)\n",
-    "    print(i)\n",
     "print(futures_list)"
    ]
   },
@@ -210,6 +220,45 @@
     "Note the difference between CPU times and wall clock?"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Another way to do this is using list comprehension"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%time\n",
+    "\n",
+    "futures_list = [slow_function.remote() for _ in range(4)]\n",
+    "futures_list"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%time\n",
+    "\n",
+    "values_list = [ray.get(future) for future in futures_list]\n",
+    "values_list"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Note the difference between CPU times and wall clock in comprehensions? \n",
+    "Comprehensions seems faster."
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -240,13 +289,16 @@
    "source": [
     "[*Patterns for Parallel Programming*](https://www.goodreads.com/book/show/85053.Patterns_for_Parallel_Programming)  \n",
     "Timothy G. Mattson, Beverly A. Sanders, Berna L. Massingill  \n",
-    "Addison-Wesley (2004)"
+    "Addison-Wesley (2004)\n",
+    "\n",
+    "[Ray Core Walkthrough](https://docs.ray.io/en/latest/walkthrough.html)\n",
+    "Ray Documentation and Gettting started materials"
    ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -260,7 +312,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.8"
+   "version": "3.7.11"
   }
  },
  "nbformat": 4,