Category: Benchmarks
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Optimizing an NVFP4 Blockscaled GEMM on RTX PRO 6000 Blackwell GPU (SM120)
This article is a continuation of our series on NVFP4 blockscaling on SM12x GPUs. In Part 1, we covered relevant PTX instructions, scale-factor layout details, and implementation details in CuTe DSL, including how to convert a CUTLASS dense GEMM example into an NVFP4 blockscaled GEMM. In this article, we optimize the NVFP4 GEMM from Part… Go to article…
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FlashAttention-3 for Inference: INT8 Quantization and Query Head Packing for MQA/GQA (External)
In this blog post presented on the Character.AI research blog, we explain two techniques that are important for using FlashAttention-3 for inference: in-kernel pre-processing of tensors via warp specialization and query head packing for MQA/GQA. Go to article…
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Sharing NVIDIA® GPUs at the System Level: Time-Sliced and MIG-Backed vGPUs
While some modern applications for GPUs aim to consume all GPU resources and even scale to multiple GPUs (deep learning training, for instance), other applications require only a fraction of GPU resources (like some deep learning inferencing) or don’t use GPUs all the time (for example, a developer working on an NVIDIA CUDA® application may… Go to article…