Mixed-criticality (MC) scheduling of sequential tasks (with no intra-task parallelism) has been well-explored by the real-time systems community. However, till date, there has been little progress on MC scheduling of parallel tasks. MC scheduling of parallel tasks is highly challenging due to the requirement of various assurances under different criticality levels. In this work, we address the MC scheduling of parallel tasks of gang model that allows workloads to execute on multiple cores simultaneously. Such a workload model represents an efficient mode-based parallel processing scheme with many potential applications. To schedule such task sets, we propose a new technique GEDF-VD, which integrates Global Earliest Deadline First (GEDF) and Earliest Deadline First with Virtual Deadline (EDF-VD). We prove the correctness of GEDF-VD and provide a detailed quantitative evaluation in terms of speedup bound in both the MC and the non-MC cases. Specifically, we show that GEDF provides a speedup bound of 2 for non-MC gang tasks, while the speedup for GEDF-VD considering MC gang tasks is √5 + 1. Experiments on randomly generated gang task sets are conducted to validate our theoretical findings and to demonstrate the effectiveness of the proposed approach.