Two critical points lie in applying loop pipelining in coarse-grained reconfigurable arrays. One is the technique of dynamically loop scheduling to achieve high pipeline throughput. The other is memory optimizing techniques to eliminate redundant memory accesses or to overlap memory accessing with computing. In this paper, we present the implementation techniques in LEAP, a coarse-grained reconfigurable array. We propose a speculative execution mechanism for dynamic loop scheduling with the goal of one iteration per cycle. We present the implementation techniques to support the decoupling between the token generator and the collector. We introduce implementation techniques in exploiting both data dependences of intra-iteration and inter-iteration. We design two instructions for special data reuses in the case of loop-carried dependences. The experimental results show the reduction in memory accesses reaches 72.8 times comparing with the approaches with no memory optimization in a RISC processor simulator.