#deepsparse search results

The latest #MLPerf inference results are in and they show #DeepSparse providing ~50x improvements over baseline BERT-Large reference implementation on both AWS ARM and GCP x86 instances. See how and replicate our results today: neuralmagic.com/blog/latest-ml…

RedHat_AI's tweet image. The latest #MLPerf inference results are in and they show #DeepSparse providing ~50x improvements over baseline BERT-Large reference implementation on both AWS ARM and GCP x86 instances.

See how and replicate our results today: neuralmagic.com/blog/latest-ml…

🚀 Exciting AI news from @neuralmagic! Optimize large language models effortlessly with our software and deploy them on commodity CPUs using #DeepSparse for lightning-fast inference. Unleash unparalleled performance, scalability, and cost efficiency. And get to deployment…

RedHat_AI's tweet image. 🚀 Exciting AI news from @neuralmagic! Optimize large language models effortlessly with our software and deploy them on commodity CPUs using #DeepSparse for lightning-fast inference. 

Unleash unparalleled performance, scalability, and cost efficiency. And get to deployment…

We carried a 4-core laptop around Boston, comparing runs of sparsified #YOLOv5 object detection model running on the #DeepSparse Engine and #ONNXRuntime. End result: Pruning + INT8 quantization = 10x faster and 12x smaller model. Replicate our results: neuralmagic.com/yolov5


We carried a 4-core Lenovo Yoga laptop around our home city of Boston (again!), now comparing runs of sparsified #YOLOv5 object detection model running on the #DeepSparse Engine and #ONNXRuntime. TL;DR: Pruning + INT8 quantization = 10x faster and 12x smaller YOLOv5 model.

RedHat_AI's tweet image. We carried a 4-core Lenovo Yoga laptop around our home city of Boston (again!), now comparing runs of sparsified #YOLOv5 object detection model running on the #DeepSparse Engine and #ONNXRuntime. 

TL;DR: Pruning + INT8 quantization = 10x faster and 12x smaller YOLOv5 model.

#DeepSparse Engine, a CPU runtime that delivers GPU-class performance by taking advantage of #sparsity within neural networks to reduce compute required as well as accelerate memory bound workloads. #DeepLearning #Python #OpenSource github.com/neuralmagic/de…

GuglielmoIozzia's tweet image. #DeepSparse Engine, a CPU runtime that delivers GPU-class performance by taking advantage of #sparsity within neural networks to reduce compute required as well as accelerate memory bound workloads. #DeepLearning #Python #OpenSource
github.com/neuralmagic/de…

Neural Magic #DeepSparse 1.5 Released For Faster #AI Inference On CPUs phoronix.com/news/DeepSpars…


And benchmark/deploy with 8X better performance in the freely-available #DeepSparse Engine! github.com/neuralmagic/de…


Here's the best part. In 22 days, on May 25th, @markurtz_ and @DAlistarh will show you how you can download already-optimized, open-source LLMs from the #SparseZoo and run them on CPUs at GPU speeds and better using #DeepSparse. Confirm your spot: hubs.li/Q01Nx7pB0


#DeepSparse allows you to balance between the desired latency, throughput, and cost, so you can pay the model hosting cost within your budget while achieving the preferred performance metrics.


How is all this possible? We leverage #sparsity, which allows us to reduce the computational requirements of ML models by up to 95%. But the real “magic” happens through the coupling of sparsified models with our own #DeepSparse runtime.


New Project on Gun Detection with Optimized DeepSparse YOLOv5 Model only at the Augmented Startups AI Project Store. 🚀lnkd.in/dH2fjrw7 #deepsparse Neural Magic #computervision #opencv #gunviolence #stopgunviolence lnkd.in/dUzm_6-N


The latest #MLPerf inference results are in and they show #DeepSparse providing ~50x improvements over baseline BERT-Large reference implementation on both AWS ARM and GCP x86 instances. See how and replicate our results today: neuralmagic.com/blog/latest-ml…

RedHat_AI's tweet image. The latest #MLPerf inference results are in and they show #DeepSparse providing ~50x improvements over baseline BERT-Large reference implementation on both AWS ARM and GCP x86 instances.

See how and replicate our results today: neuralmagic.com/blog/latest-ml…

🚀 Exciting AI news from @neuralmagic! Optimize large language models effortlessly with our software and deploy them on commodity CPUs using #DeepSparse for lightning-fast inference. Unleash unparalleled performance, scalability, and cost efficiency. And get to deployment…

RedHat_AI's tweet image. 🚀 Exciting AI news from @neuralmagic! Optimize large language models effortlessly with our software and deploy them on commodity CPUs using #DeepSparse for lightning-fast inference. 

Unleash unparalleled performance, scalability, and cost efficiency. And get to deployment…

Neural Magic #DeepSparse 1.5 Released For Faster #AI Inference On CPUs phoronix.com/news/DeepSpars…


Here's the best part. In 22 days, on May 25th, @markurtz_ and @DAlistarh will show you how you can download already-optimized, open-source LLMs from the #SparseZoo and run them on CPUs at GPU speeds and better using #DeepSparse. Confirm your spot: hubs.li/Q01Nx7pB0


#DeepSparse allows you to balance between the desired latency, throughput, and cost, so you can pay the model hosting cost within your budget while achieving the preferred performance metrics.


How is all this possible? We leverage #sparsity, which allows us to reduce the computational requirements of ML models by up to 95%. But the real “magic” happens through the coupling of sparsified models with our own #DeepSparse runtime.


New Project on Gun Detection with Optimized DeepSparse YOLOv5 Model only at the Augmented Startups AI Project Store. 🚀lnkd.in/dH2fjrw7 #deepsparse Neural Magic #computervision #opencv #gunviolence #stopgunviolence lnkd.in/dUzm_6-N


And benchmark/deploy with 8X better performance in the freely-available #DeepSparse Engine! github.com/neuralmagic/de…


We carried a 4-core laptop around Boston, comparing runs of sparsified #YOLOv5 object detection model running on the #DeepSparse Engine and #ONNXRuntime. End result: Pruning + INT8 quantization = 10x faster and 12x smaller model. Replicate our results: neuralmagic.com/yolov5


We carried a 4-core Lenovo Yoga laptop around our home city of Boston (again!), now comparing runs of sparsified #YOLOv5 object detection model running on the #DeepSparse Engine and #ONNXRuntime. TL;DR: Pruning + INT8 quantization = 10x faster and 12x smaller YOLOv5 model.

RedHat_AI's tweet image. We carried a 4-core Lenovo Yoga laptop around our home city of Boston (again!), now comparing runs of sparsified #YOLOv5 object detection model running on the #DeepSparse Engine and #ONNXRuntime. 

TL;DR: Pruning + INT8 quantization = 10x faster and 12x smaller YOLOv5 model.

#DeepSparse Engine, a CPU runtime that delivers GPU-class performance by taking advantage of #sparsity within neural networks to reduce compute required as well as accelerate memory bound workloads. #DeepLearning #Python #OpenSource github.com/neuralmagic/de…

GuglielmoIozzia's tweet image. #DeepSparse Engine, a CPU runtime that delivers GPU-class performance by taking advantage of #sparsity within neural networks to reduce compute required as well as accelerate memory bound workloads. #DeepLearning #Python #OpenSource
github.com/neuralmagic/de…

No results for "#deepsparse"

🚀 Exciting AI news from @neuralmagic! Optimize large language models effortlessly with our software and deploy them on commodity CPUs using #DeepSparse for lightning-fast inference. Unleash unparalleled performance, scalability, and cost efficiency. And get to deployment…

RedHat_AI's tweet image. 🚀 Exciting AI news from @neuralmagic! Optimize large language models effortlessly with our software and deploy them on commodity CPUs using #DeepSparse for lightning-fast inference. 

Unleash unparalleled performance, scalability, and cost efficiency. And get to deployment…

The latest #MLPerf inference results are in and they show #DeepSparse providing ~50x improvements over baseline BERT-Large reference implementation on both AWS ARM and GCP x86 instances. See how and replicate our results today: neuralmagic.com/blog/latest-ml…

RedHat_AI's tweet image. The latest #MLPerf inference results are in and they show #DeepSparse providing ~50x improvements over baseline BERT-Large reference implementation on both AWS ARM and GCP x86 instances.

See how and replicate our results today: neuralmagic.com/blog/latest-ml…

#DeepSparse Engine, a CPU runtime that delivers GPU-class performance by taking advantage of #sparsity within neural networks to reduce compute required as well as accelerate memory bound workloads. #DeepLearning #Python #OpenSource github.com/neuralmagic/de…

GuglielmoIozzia's tweet image. #DeepSparse Engine, a CPU runtime that delivers GPU-class performance by taking advantage of #sparsity within neural networks to reduce compute required as well as accelerate memory bound workloads. #DeepLearning #Python #OpenSource
github.com/neuralmagic/de…

We carried a 4-core Lenovo Yoga laptop around our home city of Boston (again!), now comparing runs of sparsified #YOLOv5 object detection model running on the #DeepSparse Engine and #ONNXRuntime. TL;DR: Pruning + INT8 quantization = 10x faster and 12x smaller YOLOv5 model.

RedHat_AI's tweet image. We carried a 4-core Lenovo Yoga laptop around our home city of Boston (again!), now comparing runs of sparsified #YOLOv5 object detection model running on the #DeepSparse Engine and #ONNXRuntime. 

TL;DR: Pruning + INT8 quantization = 10x faster and 12x smaller YOLOv5 model.

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