Formal Synthesis and Code Generation of Embedded Real-Time Software Pao-Ann Hsiung National Chung Cheng University Chiayi-621, Taiwan, ROC. 9th ACM/IEEE International Symposium on Hardware- Software Codesign, Copenhagen, Denmark, April 25-27, 2001.

2 Contents  Embedded Real-Time Software  Model and Problem  Synthesis Algorithm  Code Generation  Example  Conclusions

3 Embedded Real-Time Software  Two Main Issues:  Real-Time Constraints  Bounded Memory Execution Quasi-Static Data Scheduling (QSDS) Dynamic Real-Time Scheduling (DRTS) Proposed Solutions

4 Model Time Free-Choice Petri Nets (TFCPN) Each arc from a place is either a unique outgoing arc or a unique incoming arc to a transition.

5 Synthesis Problem  Given a set of TFCPNs, an upper-bound on memory use, and a set of real-time constraints, a software code is to be generated such that: 1) it can be executed on a single processor, 2) its memory usage does not exceed the upper bound, and 3) it satisfies all real-time constraints.

6 Synthesis Algorithm  ERTS_Synth(S, , E) {  // Quasi-Static Data Scheduling (QSDS)  for each A i in S {  B i = CF_generate (A i ); // B i: set of CF components  for each CF component A ij in B i {  QSS ij = quasi_static_schedule (A ij,  );  if QSS ij = NULL { print “QSDS failed for A ij ”; return QError;}  else QSS i = QSS i  {QSS ij } ; } }  // Dynamic Real-Time Scheduling (DRTS)  RTS = real_time_schedule (QSS 1,…,QSS n, B 1,…,B n, E );  if RTS = NULL {  print “DRTS failed for S”; return DRTS_Error; }  else generate_code (S, QSS 1,…, QSS n,RTS );  return Synthesized; }

7 Quasi-Static Data Scheduling TFCPN net decomposition Conflict-Free Components Finite Complete Cycle Deadlock-Free Quasi-Static Data Scheduled CF-Components

8 Dynamic Real-Time Scheduling  Single Processor  Rate-Monotonic Scheduling  Earliest Deadline First Scheduling  Worst Case Timing Analysis for each TFCPN

9 Code Generation  generate_code(S, QSS 1, QSS 2, …, QSS n, RTS) {  for i = 1, …, n {  D i = create_process(QSS i );  for j = 1, …, IFR(A i ) {  d ij = create_task(QSS i );  generate_task_code ( d ij );  add_task ( d ij, D i ); } }  create_main() ;  output “ for(i=0, i<length(RTS); i++) { ”;  for k = 1, …, RTS output_code ( D ik );  output “ } ”; } IFR(A i ): # transitions in A i with independent firing rates

10 Optimal Code Hierarchy Main Program Process i Task 1Task 2Task k … Source Transitions in TFCPN

11 Task Code Generation  generate_task_code(d ij ) {  output t 0 ; // t 0 : source transition  for each ICF sub-component d ijk in d ij {  for l = 1, …, u k {  if t l is visited continue;  if t l is a conflicting transition in T i {  if p = in_place(t l ) not visited  output “ switch(p){ ”;  else output “ break; ”;  output “ case t l : call t l ; ”;  for all p = out_place(t l )  output “ count(p’)+=F(t(l),p’); ”;  times_visited p ++; }

12 Task Code Generation (contd.)  if NumFire (t l ) < NumFire (t l-1 ) {  output “ if(count(p)>=F(p,t l ) {call t l ; ”;  output “ count(p)  =NumFire(t(l  1)); } ”; }  if NumFire (t l ) > NumFire (t l-1 ) {  output “ while(count(p)>=F(p,t l )){call t l ; ”;  for all p = in_place(t l )  output “ count(p)  =F(p, t l ); ”;  output “ } ”; }  if NumFire (t l ) = NumFire (t l-1 ) {  output “ count(p)  = F(p, t l ); call t l ”;  output “ count(p) += F(t l,p); ”; }  if times_visited p = num_choice (p)  output “ } ”; } } }

13 Example S = {F 1, F 2 }

14 Conflict Free Components for F 1 v 12 = (t 11, t 13, t 15, t 15 ) 13   (v 12 )  26 Quasi-Static Data Scheduling v 11 = (t 11, t 12, t 11, t 12, t 14 ) 11   (v 11 )  22

15 Conflict Free Components for F 2 v 21 = (t 21, t 22, 2t 24, 4t 26, t 28, t 29, t 26 ) 31   (v 21 )  68 v 22 = (t 21, t 23, t 25, 2t 27, t 28, t 29, t 26 ) 15   (v 22 )  36 Quasi-Static Data Scheduling

16 Dynamic Real-Time Scheduling TaskPriority ii  max (  1 )  max (  2 ) T1T T2T SchedulableYesNo AlgorithmsRM, EDF  1 = {v 11, v 12 }  2 = {v 12, t 11 t 12 k  v 12 t 11 t 12 t 14, k  1}

17 ERTS Code for task 11  task 11 ( ) { // d 11 = {t 11, t 12, t 14, t 13, t 15 }  call t 11 ;  switch( p 1 ) {  case t 12 : call t 12 ; coun t(p 2 ) + = 1;  if(coun t(p 2 )  2)  { call t 14 ; coun t(p 2 )  = 2; }  break;  case t 13 : call t 13 ; coun t(p 3 ) += 2;  whil e(count(p 3 )  1)  { call t 15 ; coun t(p 3 )  =1; }  break; }  }

18 ERTS Code for task 21  task 21 ( ) { // d 21 = {t 21, t 22, t 24, t 26, t 23, t 25, t 27 }  call t 21 ;  switch( p 1 ) {  case t 22 : call t 22 ; coun t(p 2 ) += 2;  while(coun t(p 2 )  1) {  coun t(p 4 ) += 2; call t 24 ; coun t(p 2 )  =1;}  while(coun t(p 4 )  1) {  call t 26 ; coun t(p 4 )  =1;} break;  case t 23 :call t 23 ; coun t(p 3 ) += 1; coun t(p 3 )  =1;  call t 25 ; coun t(p 5 ) += 2; coun t(p 6 ) += 2;  whil e (coun t(p 5 )  1  coun t(p 6 )  1) {  call t 27 ; coun t(p 5 )  =1; coun t(p 6 )  =1; }  break; } }

19 ERTS Code for task 22 and main()  task 22 ( ) { // d 22 = {t 28, t 29, t 26 }  call t 28 ; call t 29 ; call t 26 ;  }  main( ) {  k 11 = k 21 = k 22 = 0 ;// iteration numbers  while true {  if(now()  11  k 11  100) { task 11 ( ); k 11 ++;}  if(now()  21  k 21  110) { task 21 ( ); k 21 ++;}  if(now()  22  k 22  110) { task 22 ( ); k 22 ++;} }  }

20 Conclusions  An algorithm proposed for synthesizing Embedded Real-Time Software  Bounded Memory Execution  Quasi-Static Data Scheduling  Real-Time Constraints  Dynamic Real-Time Scheduling  Code Generation  Optimal # of tasks  Future Work: Exception Handling, Verification, Theory on Separation of Concerns