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\section{Adjoint dump \& restart -- divided adjoint (DIVA) |
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\label{sec_ad_diva}} |
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{\it Patrick Heimbach \& Geoffrey Gebbie, MIT/EAPS, 07-Mar-2003} |
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|
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{\bf |
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NOTE: \\ |
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THIS SECTION IS SUBJECT TO CHANGE. |
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IT REFERS TO TAF-1.4.26. |
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Previous TAF versions are incomplete and have problems |
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with both TAF options '-pure' and '-mpi'. |
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|
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The code which is tuned to the DIVA implementation |
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of this TAF version |
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is {\it checkpoint50} (MITgcm) and {\it ecco\_c50\_e28} (ECCO). |
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} |
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\subsection{Introduction} |
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Most high performance computing (HPC) centres require the use |
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of batch jobs for code execution. |
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Limits in maximum available CPU time and memory may prevent |
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the adjoint code execution from fitting into any of the available |
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queues. This presents a serious limit for large scale / |
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long time adjoint ocean and climate model integrations. |
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The MITgcm itself enables the split of the total model |
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integration into sub-intervals through standard dump/restart |
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of/from the full model state. |
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For a similar procedure to run in reverse mode, |
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the adjoint model requires, in addition to the model state, |
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the adjoint model state, |
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i.e. all variables with derivative information |
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which are needed in an adjoint restart. |
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This adjoint dump \& restart is also termed 'divided adjoint (DIVA). |
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|
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For this to work in conjunction with automatic differentiation, |
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an AD tool needs to perform the following tasks: |
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% |
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\begin{enumerate} |
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% |
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\item |
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% |
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identify an adjoint state, i.e. those sensitivities whose |
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accumulation is interrupted by a dump/restart and which influence |
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the outcome of the gradient. |
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Ideally, this state consists of |
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% |
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\begin{itemize} |
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% |
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\item |
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the adjoint of the model state, |
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% |
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\item |
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the adjoint of other intermediate results (such as control variables, |
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cost function contributions, etc.) |
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% |
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\item |
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bookkeeping indices (such as loop indices, etc.) |
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% |
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\end{itemize} |
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% |
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\item |
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% |
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generate code for storing and reading adjoint state variables |
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% |
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\item |
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generate code for bookkeeping , i.e. maintaining a file |
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with index information |
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% |
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\item |
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generate a suitable adjoint loop to propagate adjoint values |
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for dump/restart with a minimum overhad of adjoint intermediate |
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values. |
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% |
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\end{enumerate} |
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|
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TAF (but not TAMC!) |
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generates adjoint code which performs the above specified |
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tasks. It is closely tied to the adjoint multi-level checkpointing. |
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The adjoint state is dumped (and restarted) at each step of the |
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outermost checkpointing level and adjoint intergration is performed |
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over one outermost checkpointing interval. |
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Prior to the adjoint computations, a full foward sweep is performed to |
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generate the outermost (forward state) tapes and to calculate |
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the cost function. |
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In the current implementation, the forward sweep is |
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immediately followed by the first adjoint leg. |
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Thus, in theory, the following steps are performed (automatically) |
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% |
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\begin{itemize} |
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\item {\bf 1st model call:} \\ |
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This is the case if file {\tt costfinal} does {\it not} exist. |
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S/R {\tt mdthe\_main\_loop} is called. |
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% |
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\begin{enumerate} |
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% |
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\item |
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calculate forward trajectory and dump model state after each |
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outermost checkpointing interval to files {\tt tapelev3} |
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% |
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\item |
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calculate cost function {\tt fc} and write it to file |
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{\tt costfinal} |
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\end{enumerate} |
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% |
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\item{\bf 2nd and all remaining model call:} \\ |
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This is the case if file {\tt costfinal} {\it does} exist. |
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S/R {\tt adthe\_main\_loop} is called. |
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% |
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\begin{enumerate} |
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% |
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\item |
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(forward run and cost function call is avoided |
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since all values are known) |
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\begin{itemize} |
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\item |
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if 1st adjoint leg: \\ |
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create index file {\tt divided.ctrl} which contains |
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info on current checkpointing index $ilev3$ |
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% |
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\item |
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if not $i$-th adjoint leg: \\ |
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adjoint picks up at $ilev3 = nlev3-i+1$ and runs to $nlev3 - i$ |
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\end{itemize} |
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\item |
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perform adjoint leg from $nlev3-i+1$ to $nlev3 - i$ |
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\item |
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dump adjoint state to file {\tt snapshot} |
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\item |
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dump index file {\tt divided.ctrl} for next adjoint leg |
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\item |
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in the last step the gradient is written. |
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\end{enumerate} |
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\end{itemize} |
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A few modififications were performed in the forward code, |
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obvious ones such as adding the corresponding TAF-directive |
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at the appropriate place, and less obvious ones |
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(avoid some re-initializations, when in an intermediate |
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adjoint integration interval). |
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|
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[For TAF-1.4.20 a number of hand-modifications were necessary |
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to compensate for TAF bugs. |
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Since we refer to TAF-1.4.26 onwards, |
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these modifications are not documented here]. |
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\subsection{Recipe 1: single processor} |
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\begin{enumerate} |
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\item |
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In {\tt ECCO\_CPPOPTIONS.h} set: |
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% |
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{\footnotesize |
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\begin{verbatim} |
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#define ALLOW_DIVIDED_ADJOINT |
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#undef ALLOW_DIVIDED_ADJOINT_MPI |
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\end{verbatim} |
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} |
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\item |
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Generate adjoint code. |
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Using the TAF option '{\tt -pure}', two codes are generated: |
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% |
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\begin{itemize} |
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% |
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\item {\tt mdthe\_main\_loop}: \\ |
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Is responsible for the forward trajectory, storing of outermost |
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checkpoint levels to file, computation of cost function, and |
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storing of cost function to file (1st step). |
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% |
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\item {\tt adthe\_main\_loop}: \\ |
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Is responsible for computing one adjoint leg, dump adjoint state |
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to file and write index info to file (2nd and consecutive steps). |
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|
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for adjoint code generation, e.g. add '{\tt -pure}' to |
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TAF option list |
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{\footnotesize |
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\begin{verbatim} |
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make adtaf |
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\end{verbatim} |
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} |
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% |
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|
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\item |
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One modification needs to be made to adjoint codes in |
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S/R adecco\_the\_main\_loop: |
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There's a remaining issue with the '{\tt -pure}' option. |
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The '{\tt call ad...}' |
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between '{\tt call ad...}' and the read of the {\tt snapshot} file |
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should be called only in the firt adjoint leg between |
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$nlev3$ and $nlev3-1$. |
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In the ecco-branch, the following lines should be |
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bracketed by an {\tt if (idivbeg .GE. nchklev\_3) then}, thus: |
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|
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{\footnotesize |
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\begin{verbatim} |
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|
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... |
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xx_psbar_mean_dummy = onetape_xx_psbar_mean_dummy_3h(1) |
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xx_tbar_mean_dummy = onetape_xx_tbar_mean_dummy_4h(1) |
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xx_sbar_mean_dummy = onetape_xx_sbar_mean_dummy_5h(1) |
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call barrier( mythid ) |
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cAdd( |
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if (idivbeg .GE. nchklev_3) then |
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cAdd) |
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|
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call adcost_final( mythid ) |
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call barrier( mythid ) |
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call adcost_sst( mythid ) |
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call adcost_ssh( mythid ) |
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call adcost_hyd( mythid ) |
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call adcost_averagesfields( mytime,myiter,mythid ) |
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call barrier( mythid ) |
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cAdd( |
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endif |
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cAdd) |
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|
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C---------------------------------------------- |
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C read snapshot |
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C---------------------------------------------- |
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if (idivbeg .lt. nchklev_3) then |
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open(unit=77,file='snapshot',status='old',form='unformatted', |
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$iostat=iers) |
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... |
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|
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\end{verbatim} |
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} |
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For the main code, in all likelihood the block which needs to |
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be bracketed consists of {\tt adcost\_final} only. |
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|
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\item |
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Now the code can be copied as usual to {\tt adjoint\_model.F} |
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and then be compiled: |
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% |
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{\footnotesize |
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\begin{verbatim} |
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make adchange |
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then compile |
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\end{verbatim} |
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} |
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|
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\end{itemize} |
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|
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\end{enumerate} |
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\subsection{Recipe 2: multi processor (MPI)} |
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|
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\begin{enumerate} |
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\item |
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On the machine where you execute the code |
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(most likely not the machine where you run TAF) |
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find the includes directory for MPI containing {\tt mpif.h}. |
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Either copy {\tt mpif.h} to the machine where you generate the |
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{\tt .f} files before TAF-ing, or add the path to the includes |
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directory to you genmake {\tt platform} setup, |
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TAF needs some MPI parameter settings |
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(essentially {\tt mpi\_comm\_world} and {\tt mpi\_integer}) |
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to incorporate those in the adjoint code. |
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|
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\item |
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In {\tt ECCO\_CPPOPTIONS.h} set |
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% |
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{\footnotesize |
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\begin{verbatim} |
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#define ALLOW_DIVIDED_ADJOINT |
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#define ALLOW_DIVIDED_ADJOINT_MPI |
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\end{verbatim} |
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} |
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% |
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This will include the header file {\tt mpif.h} |
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into the top level routine for TAF. |
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|
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\item |
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Add the TAF option '{\tt -mpi}' to the TAF argument list in the makefile. |
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|
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\item |
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Follow the same steps as in {\bf Recipe 1} (previous section). |
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|
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\end{enumerate} |
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|
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That's it. Good luck \& have fun. |
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