Grid computing is becoming the natural way to aggregate and share large sets of heterogeneous resources. With the infrastructure becoming ready for the challenge, current grid development and acceptance hinge on proving that grids reliably support real applications, and on creating adequate benchmarks to quantify this support. However, grid applications are just beginning to emerge, and traditional benchmarks have yet to prove representative in grid environments. To address this chicken-and-egg problem, we propose a middle-way approach: create and run synthetic grid workloads comprising applications representative for today?s grids. For this purpose, we have designed and implemented GRENCHMARK, a framework for synthetic workload generation and submission. The framework greatly facilitates synthetic workload modeling, comes with over 35 synthetic and real applications, and is extensible and flexible. We show how the framework can be used for grid system analysis, functionality testing in grid environments, and for comparing different grid settings, and present the results obtained with GRENCHMARK in our multi-cluster grid, the DAS