Fix emphasizing modular scheduler names

doc/doxygen/chapters/320_scheduling.doxy

@@ -127,8 +127,6 @@ The <b>peager</b> (parallel eager) scheduler is similar to eager, it also
 supports parallel tasks (still experimental). Should not be used when several 
 contexts using it are being executed simultaneously.
 
-TODO: describe modular schedulers
-
 \section TaskDistributionVsDataTransfer Task Distribution Vs Data Transfer
 
 Distributing tasks to balance the load induces data transfer penalty. StarPU
@@ -204,25 +202,25 @@ StarPU provides a powerful way to implement schedulers, as documented in \ref
 DefiningANewModularSchedulingPolicy . It is currently shipped with the following
 pre-defined Modularized Schedulers :
 
-- Eager-based Schedulers (with/without prefetching : \c modular-eager ,
-\c modular-eager-prefetching) : \n
+- Eager-based Schedulers (with/without prefetching : <b>modular-eager</b> ,
+<b>modular-eager-prefetching</b>) : \n
 Naive scheduler, which tries to map a task on the first available resource
 it finds. The prefecthing variant queues several tasks in advance to be able to
 do data prefetching. This may however degrade load balancing a bit.
 
 - Prio-based Schedulers (with/without prefetching :
-\c modular-prio, \c modular-prio-prefetching , \c modular-eager-prio) : \n
+<b>modular-prio</b>, <b>modular-prio-prefetching</b>, <b>modular-eager-prio</b>) : \n
 Similar to Eager-Based Schedulers. Can handle tasks which have a defined
 priority and schedule them accordingly.
-The \c modular-eager-prio variant integrates the eager and priority queue in a
+The <b>modular-eager-prio</b> variant integrates the eager and priority queue in a
 single component. This allows it to do a better job at pushing tasks.
 
-- Random-based Schedulers (with/without prefetching: \c modular-random,
-\c modular-random-prio, \c modular-random-prefetching, \c
-modular-random-prio-prefetching) : \n
+- Random-based Schedulers (with/without prefetching: <b>modular-random</b>,
+<b>modular-random-prio</b>, <b>modular-random-prefetching</b>,
+<b>modular-random-prio-prefetching</b>) : \n
 Selects randomly a resource to be mapped on for each task.
 
-- Work Stealing (\c modular-ws) : \n
+- Work Stealing (<b>modular-ws</b>) : \n
 Maps tasks to workers in round robin, but allows workers to steal work from other workers.
 
 - HEFT Scheduler : \n
@@ -231,14 +229,14 @@ Heterogeneous Earliest Finish Time.
 It needs that every task submitted to StarPU have a
 defined performance model (\ref PerformanceModelCalibration)
 to work efficiently, but can handle tasks without a performance
-model. \c modular-heft just takes tasks by priority order. \c modular-heft takes
-at most 5 tasks of the same priority and checks which one fits best. \c
-modular-heft-prio is similar to \c modular-heft, but only decides the memory
+model. <b>modular-heft</b> just takes tasks by priority order. <b>modular-heft</b> takes
+at most 5 tasks of the same priority and checks which one fits best.
+<b>modular-heft-prio</b> is similar to <b>modular-heft</b>, but only decides the memory
 node, not the exact worker, just pushing tasks to one central queue per memory
 node.
 
 - Heteroprio Scheduler: \n
-Maps tasks to worker similarly to HEFT, but first attribute accelerated tasks to
+<b>modular-heteroprio</b>Maps tasks to worker similarly to HEFT, but first attribute accelerated tasks to
 GPUs, then not-so-accelerated tasks to CPUs.
 
 To use one of these schedulers, one can set the environment variable \ref STARPU_SCHED.