slides update & adapt link in sessions

pages/src/sessions.md

@@ -6,7 +6,7 @@ This tutorial has been given at the following events:
 
 - 03/06/2024 - [FlexScience@HPDC24](https://sites.google.com/view/flexscience) - Quentin Guilloteau ([`030624-flexscience`](https://gitlab.inria.fr/control-for-computing/tutorial/-/tree/030624-flexscience))
 
-- 14/03/2024 - ANR ADAPT 2024 - Sophie Cerf ([`140324-adapt`](https://gitlab.inria.fr/control-for-computing/tutorial/-/tree/140324-adapt))
+- 14/03/2024 - [ANR ADAPT 2024](https://projects.femto-st.fr/ANR-ADAPT/welcome-adapt) - Sophie Cerf ([`140324-adapt`](https://gitlab.inria.fr/control-for-computing/tutorial/-/tree/140324-adapt))
 
 - 13/12/2023 - [VELVET 2023](https://helene-coullon.fr/pages/velvet/) - Sophie Cerf ([`131223-velvet`](https://gitlab.inria.fr/control-for-computing/tutorial/-/tree/131223-velvet))
 

slides/main.md

@@ -79,26 +79,26 @@ header-includes:
 
   - $\rightsquigarrow$ need for runtime management
   
-- Usual approaches:
+- Common approaches:
 
-  - adhoc policies
-  
-    - *if this then that*
-    
-    - very arbitrary constants
-    
-    - no guarantee
-
-  - or model and configure offline
+  - model and configure offline
   
     - optimal problem solving
     
     - very complex
     
     - difficult to apprehend runtime events 
+   
+  - adhoc runtime policies
+  
+    - *if this then that*
+    
+    - very arbitrary constants
+    
+    - no guarantee
 
 \begin{center}
-\textbf{We need another approach:} with guarantees, simple, and robust to runtime variations.)
+\textbf{We need another approach:} with guarantees, simple, and robust to runtime variations
 \end{center}
   
 
@@ -131,7 +131,6 @@ Use the measurement of relevant system metrics to adapt its configuration
 
 - Separation of concerns
 
-- $\neq$ implementations of AC (rules, AI, **control**)
 
 
 :::
@@ -144,7 +143,7 @@ Use the measurement of relevant system metrics to adapt its configuration
 
 Use the measurement of relevant system metrics to adapt its configuration
 
-## Autonomic Computing (IBM 2003)
+## Autonomic Computing
 
 :::::::::::::: {.columns}
 ::: {.column width="50%"}
@@ -194,6 +193,8 @@ Soundly act on a system based on its measurements, to reach a desired behavior
 :::
 ::: {.column width="50%"}
 
+- Handles dynamic behavior
+
 - Proven Guarantees
 
   - Stability
@@ -215,9 +216,9 @@ Soundly act on a system based on its measurements, to reach a desired behavior
 
 
 
-# The (famous) PID Controller (discretized)
+# Control Theory Formulation in 1 slide
 
-\begin{block}{First, \textbf{a Model ...} (i.e., how does the system behave (Open-Loop))}
+\begin{block}{First, \textbf{a Dynamic Model ...} (i.e., how does the system behave)}
 
 \begin{center}
 \scalebox{0.85}{
@@ -272,7 +273,7 @@ The controller gains define this behavior!
 ## Goal
 
 \begin{center}
-Map the error to the next action to reach desired system state with guarantees
+Map the error to the next action, to reach desired system state with guaranted behavior
 \end{center}
 
 ## Many (many) types of Controllers
@@ -294,7 +295,7 @@ Map the error to the next action to reach desired system state with guarantees
 # Methodology
 
 
-![Control Theory Methodology](figs/methodo.pdf){width=90% height=50%}
+![Control Theory Methodology (Cerf, 2021)](figs/methodo.pdf){width=90% height=50%}
 
 <!---
 # Some Examples
@@ -329,9 +330,9 @@ Map the error to the next action to reach desired system state with guarantees
 
 - Regulate the **energy consumption of a processor** in memory-intensive phases
 
-  - Sensor: RAPL powercap
+  - Sensor: application's progess
   
-  - Actuator: application's progess
+  - Actuator: RAPL powercap
   
   - Controller: PI, Adaptive control
   
@@ -365,7 +366,7 @@ Map the error to the next action to reach desired system state with guarantees
 
 5. Perform a model identification
 
-5. Apprehend advanced control techniques (optimal, disturbance rejection)
+5. Apprehend more advanced control techniques
 
 5. **Formalize a control closed-loop of your own system**