Over the last decade, Graphics Processing Units (GPUs) have been used extensively in gaming consoles, mobile phones, workstations and data centers, as they have exhibited immense performance improvement over CPUs, in graphics intensive applications. Due to their highly parallel architecture, general purpose GPUs (GPGPUs) have gained the foreground in applications where large data blocks can be processed in parallel. However, the performance improvement is constrained by a large power consumption. Likewise, Near Threshold Computing (NTC) has emerged as an energy-efficient design paradigm. Hence, operating GPUs at NTC seems like a plausible solution to counteract the high energy consumption. This work investigates the challenges associated with NTC operation of GPUs and proposes a low-power GPU design, Split Latency Allocator, to sustain the performance of GPGPU applications.