15B模型在分梯度操作分片策略(shard_grad_op)扩展效果最好,但混合分片策略(HYBRID_8GPUs)更接近理想扩展状态。可见多节点测试时,不同的模型选择不同分片策略,可以有效提升并行效率。 以下是不同分片方式下GPU内存使用情况 总结 PyTorch可以直接在Frontier和AMD GPU上工作 为了优化性能,需要考虑Frontier的节点拓扑结构 不...
SeePre-training a large language model with Megatron-DeepSpeed on multiple AMD GPUsfor a detailed example of training with DeepSpeed on an AMD accelerator or GPU. Automatic mixed precision (AMP)# As models increase in size, so do the time and memory needed to train them; their cost also inc...
To overcome this limitation, this paper introduces a new methodology to fully characterize the impact of non-conventional DVFS on GPUs. The proposed approach was evaluated on two devices, an AMD Vega 10 Frontier Edition and an AMD Radeon 5700XT. When applying this non-conventional DVFS scheme ...
DeepSpeed SeePre-training a large language model with Megatron-DeepSpeed on multiple AMD GPUsfor a detailed example of training with DeepSpeed on an AMD accelerator or GPU. Automatic mixed precision (AMP)# As models increase in size, so do the time and memory needed to train them; their cost...
Since the introduction of AI upscaling technologies such as DLSS (Deep-learning super sampling) from Nvidia and FSR (FidelityFX super-resolution) from AMD, getting more FPS is simpler than ever. By enabling one setting in-game, users get an AI upscaled image that reduces GPU demand and enhance...
Another AMD Gaming exec. on the briefing call, Nish Neelalojanan, did explain that machine learning is still a big part of the optimisations going on with Radeon GPUs, however, and that it was still possible to achieve “the same thing with more standard frameworks.” ...
Is AMD finally going to present an AI/ML-based FSR 2.0 implementation? FSR and machine-learning based AI upscaling solutions like XeSS and DLSS 2.0 are not alike. While XeSS and DLSS 2.0 are upscaling systems based on Deep Learning/Inference and use actual hardware to enable performance enhan...
Indiana Jones and the Great Circle proves Nvidia wrong about 8GB GPUs Valve has made a significant update to its Proton compatibility layer, which is the basis of the Linux-based SteamOS operating system on the Steam Deck. The update brings several improvements and bug fixes, but it also adds...
In the previous section we talked about the memory management within machine learning software involving mostly CPU-bound workloads. Such software often relies on intermediary frameworks such as PyTorch or TensorFlow for Deep Learning which commonly abstract away all the underlying, h...
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