In the process of developing software and hardware, profiling workloads is critical. Binary Instrumentation Technology plays a key role in this task for both x86 architecture and Intel Graphics Processing Units. The GTPin framework is the first tool that allows the profiling of graphics and compute kernels running on Intel GPUs. However, GTPin capabilities are less flexible than x86 profiling tools. In this paper, we introduce the concept of “gLIT” – Long Instruction Trace for Intel GPUs. Generated on real hardware, gLIT can be replayed on a simulator or an emulator running on the CPU device, and thus, can be easily profiled and analyzed “on the fly” with analysis tools of any complexity. Since the graphics devices are extremely parallel, the gLIT trace is, by definition, a multi-threaded trace, reflecting a kernel concurrently running hundreds of hardware threads. The ability to thoroughly profile and analyze workloads is critical for improving hardware and software readiness and creates new possibilities for academic research on Intel graphics devices.

Functional and performance profiling of workloads is critical in developing software and hardware. Binary Instrumentation Technology has played a key role in this task for many years in the world of x86 architecture. However, such capabilities have not been available until recently for graphics devices, especially in the Intel Graphics Processing Unit world. The GTPin framework is the only tool that supports profiling graphics and GP-GPU kernels running on extremely parallel Intel GPU devices. GTPin supports a wide range of capabilities for software and hardware developers. With GTPin, you can profile real-world graphics and compute applications at a level of performance close to real hardware. Such an ability is critical in accelerating hardware and software readiness.