DirectML provides GPU acceleration for common machine learning tasks across a broad range of supported hardware and drivers, including all DirectX 12-capable GPUs from vendors such as AMD, Intel, NVIDIA, and Qualcomm. A custom high-end PC powered by an 8-core Intel i7-10700K and an RTX* 3070 discrete GPUĭirectML is a high-performance, hardware-accelerated DirectX 12 library for machine learning.An HP workstation powered by a 10-core Intel® Xeon®-4114 and Quadro* P1000 discrete GPU.The Dell XPS* 13 laptop powered by a 4-core Intel i7-1165G7 and Intel® Iris® X e integrated graphics.To make things more interesting, we will run our assessment on three very different systems: We will explore Intel Xᵉ architecture’s potential for multi-platform AI deployment and its performance running Microsoft DirectML and OpenVINO™ workloads. Microsoft DirectML* and Intel® Distribution of OpenVINO™ toolkit are powerful platforms which are turbocharging AI development by lowering the barrier of entry to Machine Learning. ![]() ![]() Intel® X e Powered AI Workloads in Windows* Environments In terms of performance, the Xᵉ-LP iGPU is very capable for compute scenarios and its 96 Execution Units and 1.30Ghz max running frequency translate to outstanding AI inference capabilities for its size and wattage. The Intel Xᵉ-LP iGPU lives on the same chip with the processor and utilizes a portion of the system’s memory, rather than using a dedicated DDR chip.
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