Heterogeneous computing is required in systems ranging from low-end embedded systems up to the high-end HPC systems to reach high-performance while keeping power consumption low. Having more and more accelerators and CPUs also creates challenges for the programmer, requiring even more expertise of them. Fortunately, new modern C++-based domain-specific languages, such as the SYCL open standard from Khronos Group, simplify the programming at the full system level while keeping high performance. SYCL is a single-source programming model providing a task graph of heterogeneous kernels that can be run on various accelerators or even just the CPU. The memory heterogeneity is abstracted through buffer objects and the memory usage is abstracted with accessor objects. From these accessors, the task graph is implicitly constructed, the synchronizations and the data movements across the various physical memories are done automatically, by opposition to OpenCL or CUDA. Sometimes, some applications or libraries already exist using the OpenCL standard or some OpenCL kernels are provided, either as OpenCL kernel source code or even as built-in OpenCL kernels written in RTL for extreme optimization on FPGA. SYCL provides an OpenCL interoperability mode to reuse existing OpenCL code while keeping the higher level task graph programming model without needing explicit memory transfers. We present some experiments on two applications on GPU and FPGA with the triSYCL open-source implementation to show the benefits of this OpenCL interoperability mode.