Coarse-grained　reconfigurable　arrays　(CGRAs)　can　be　dynamically　programmed　by　configuration　contexts　to　concurrently　run　multiple　operations　on　a　processing　elements　array.　This　further　widens　the　gap　between　off-chip　memory　bandwidth　demand　and　the　limited　speed　of　off-chip　memory　access.　Cache　prefetching　is　widely　used　for　mitigating　off-chip　memory　latency.　However,　straightforwardly　applying　existing　prefetching　techniques　(primarily　focusing　on　instruction　driven　processors)　to　CGRA　may　induce　inaccurate　prefetching,　thereby　crippling　CGRA　performance.　Based　on　repetitively　executed　context　in　CGRA　computing,　this　paper　proposes　a　context-directed　pattern　matching　(CDPM)　mechanism　to　improve　prefetching　accuracy　for　CGRAs.　CDPM　generates　a　prefetch　pattern　for　an　initially　executed　context,　and　then　reuses　the　pattern　to　issue　prefetch　requests　when　the　context　is　re-executed.　In　order　to　eliminate　the　outdated　prefetch　pattern,　CDPM　also　evaluates　the　prefetching　accuracy　of　the　prefetch　pattern　at　run-time　by　adding　prefetch　addresses　to　a　Bloom　filter.　The　distinguishing　feature　of　CDPM　is　the　employment　of　the　CGRA　configuration　context　as　a　guide　to　improving　prefetching　accuracy.　Experimental　results　showed　that　CDPM　prefetching　averagely　improved　performance　by　31.1%　compared　to　tests　without　prefetching　and　by　7.7%　compared　to　state-of-the-art　cache　prefetching　techniques,　while　only　incurring　slight　area　and　power　overheads.