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Innovative Solutions for Cloud Gaming, Media, Transcoding, & AI Inferencing
- 1. Supermicro Solutions Using Intel Data Center GPU Flex Series September 15, 2022 Better Faster Greener™ © 2022 Supermicro
- 2. Better Faster Greener™ © 2022 Supermicro Supermicro Solutions Using Intel® Data Center GPU Flex Series Radhika Rao Dir. Product and Business Management, Data Center GPUs Intel Corporation Thomas Jorgensen Sr. Dir. Technology Enablement Supermicro Michael Schulman Sr. Content Manager Supermicro
- 3. Better Faster Greener™ © 2022 Supermicro 3
- 4. Better Faster Greener™ © 2022 Supermicro 4 Topics To Be Covered Details About the Intel® Data Center GPU Flex Series What New Markets Does the Intel® Data Center GPU Flex Series Address
- 5. Super Flexible Data Center GPU Better Faster Greener™ © 2022 Supermicro 5 For Visual Cloud, Media and Cloud Gaming Cloud Gaming AI Edge Inferencing Media Delivery Virtual Desktop Infrastructure
- 6. Intel Data Center GPUs Better Faster Greener™ © 2022 Supermicro 6 FLEX SERIES Intel Data Center GPU Flex 140 Intel Data Center GPU Flex 170
- 7. Optimized forTCO and Density PCIe Gen 4 Cards Half Height, half length, simple Passive Cooling 2 GPUs / card Launching with Intel® Scalable Gen3 Processors See the Vision section of intel.com/performanceindex for workloads and configurations. Results may vary. FLEX SERIES 140 4 Media Engines 75W Power Envelope 8 RayTracing Units Architecture Half Height PCIe 8 Xe cores
- 8. See the Vision section of intel.com/performanceindex for workloads and configurations. Results may vary. FLEX SERIES 170 2 Media Engines 150W Power Envelope 32 RayTracing Units Architecture Full Height PCIe 32 Xe cores Optimized for Peak Performance PCIe Gen 4 Cards Full Height, ¾ length, single-wide, Passive Cooling 1 GPU / card Launching with Intel® Scalable Gen3 Processors
- 9. Cloud Gaming Better Faster Greener™ © 2022 Supermicro 9 • High density Cloud Gaming with support for Android & Windows • Up to 54 game streams per card and 540 game streams per server • Biggest 3rd party Game Engines Supported • Run Across CPU & GPU Seamlessly
- 10. Supermicro Solutions – Cloud Gaming Better Faster Greener™ © 2022 Supermicro 10 Better Faster Greener™ © 2022 Supermicro 10 X12 CloudDC: SYS-620C-TN12R Supports Up to 6 Intel Data Center GPUs Cloud Gaming
- 11. Media Processing and Delivery Better Faster Greener™ © 2022 Supermicro 11 • Industry first AV1encoding and decoding in HW • >30% distribution cost savings • 30+ 1080p HEVC & AV1 Streams per card • Industry’s biggest media frameworks supported • oneVPL library for encode/decode and processing unified API across CPU & GPU • Open-Source SW
- 12. Media Delivery Supermicro Solutions – Media Processing & Delivery Better Faster Greener™ © 2022 Supermicro 12 Better Faster Greener™ © 2022 Supermicro 12 X12 BigTwin: SYS-220BT-DNTR/HNTRX Supports Up to 8 Intel Data Center GPUs
- 13. Supermicro Solutions – Transcoding Better Faster Greener™ © 2022 Supermicro 13 Better Faster Greener™ © 2022 Supermicro 13 X12 4U 10 GPU System: SYS-420GP-TNR Supports Up to 10 Intel Data Center GPUs Media Transcoding
- 14. AI Edge Inferencing Supermicro Solutions – AI Edge Inferencing Better Faster Greener™ © 2022 Supermicro 14 Better Faster Greener™ © 2022 Supermicro 14 X12 CloudDC: SYS-620C-TN12R Supports Up to 6 Intel Data Center GPUs
- 15. Intel® Data Center GPU Flex Series Micro Architecture Better Faster Greener™ © 2022 Supermicro 15 Scalable High-Performance Graphics Architecture for visually immersive workloads Xe core Dedicated RayTracing Units 16 Vector Engines 16 XMX Engines
- 16. Better Faster Greener™ © 2022 Supermicro 16 Intel® Data Center GPU Flex Series 140 Intel Data Center GPU Flex Series 170 Card Form Factor Half height, half length, single wide, passive cooling Full height, three-quarter length, single wide, passive cooling Card TDP 75 watts 150 watts GPUs per Card 2 1 GPU Microarchitecture Xe HPG Xe Cores 16 (8 per GPU) 32 Fixed Function Media 4 (2 per GPU) 2 Systolic Arrays (Relative) 1x 2.5x Ray Tracing Yes Peak Compute (Systolic) 8 TFLOPS (FP32) / 105 TOPS (INT8) 16 TFLOPS (FP32) / 250 TOPS (INT8) Cache 8 MB 16 MB Memory Type GDDR6 Memory Capacity 12 GB (6 per GPU) 16 GB Memory Bandwidth 300 GB/s (150 per GPU) 600 GB/s Memory Bus Width 192 bits (96 per GPU) 256 bits Virtualization (Instances)6 SR-IOV (62) SR-IOV (31) Host Bus PCIe Gen 4 Host CPU Support 3rd Generation Intel Xeon® Scalable Processors FLEX SERIES Intel Data Center GPU Flex 140 Intel Data Center GPU Flex 170
- 18. Next Gen Video Experiences: AV1 on Intel® Data Center GPU Flex Series Ushering in a new era of video with groundbreaking AV1 codec technology Intel is leading the industry in bringing a suite of AV1 solutions to the market Ultimate quality and performance optimized SVT- AV1 CPU Software Encoder for Intel® Xeon™ and Core™ processors Intel® Data Center GPU Flex Series bringing professional quality, performance AV1 HW Encode to serve Data Center
- 19. Targeted Usages Object Classification Object Detection Image Segmentation Frameworks Media AVC/HEVC/AV1 JPEG/MJPEG Upto 4k Visual Inference, Media Analytics on Intel® Data Center GPU Flex Series Xe Matrix Extensions Dedicated built-inAI functionality Accelerating most AI DataTypes 256 INT8 ops/clock 128 FP16/BF16 ops/clock 512 INT4/INT2 ops/clock
- 20. Virtual Desktop Infrastructure Better Faster Greener™ © 2022 Supermicro 20 • High density distributed virtual desktops • Up to 62 virtual functions SRIOV • No additional Virtualization costs for GPU SW licensing
- 21. Virtual Desktop Infrastructure Supermicro Solutions – Virtual Desktop Infrastructure Better Faster Greener™ © 2022 Supermicro 21 Better Faster Greener™ © 2022 Supermicro 21 X12 BigTwin: SYS-220BT-DNTR/HNTRX Supports Up to 8 Intel Data Center GPUs
- 22. Summary Better Faster Greener™ © 2022 Supermicro 22
- 23. Q & A Learn More at https://www.supermicro.com/en/accelerators/intel
- 25. Intel Data Center GPUs Better Faster Greener™ © 2022 Supermicro 25 Video Transcoding Cloud Gaming VDI AI Inference 30+ 1080p streams 40+ Game streams 62 Virtualized functions 150 AI TOPS 4 Xe Media Engines 32 Xe Core & Ray Tracing Units AV1 HW Encode & Decode XMX AI Acceleration Built in Peak Performance Intel Data Center GPU 140 (75W) Maximum Density Intel Data Center GPU 170 (150W)
Notas del editor
- Let’s first talk about the ATS-M150 optimized for peak performance.
- Let’s first talk about the ATS-M150 optimized for peak performance.
- As I said great HW needs great SW. Intel Extensible and Open Software Architecture is focusing on optimizing end-to-end workloads. Starting with low level GPU drivers and firmware, Intel’s OneAPI foundational layer, through use case specific open-source enablement of video, inference and gaming frameworks and APIs. Resulting in creation of reference solutions for our partners.
- Video streaming currently accounts for over 80% of global internet traffic which drives significant demand for video processing in the datacenter and increases cost for service providers. Providers are looking to simultaneously improve bitrate savings to keep costs low, while maintaining the visual quality needed to satisfy their customers. Arctic Sound-M is well positioned to help solve this challenge, bringing its industry leading AV1 HW encoder paired with Intel’s oneVPL library to the market later this year. ATSM with AV1 will deliver close to 30% distribution cost savings, which in todays market could translate to about $20M per year savings for 100K users.
- Currently inference solutions are on a CPU and GPU in a closed ecosystem. We have been working with customers to be able to seamless move their workloads to all Intel open source ecosystem. There are three major buckets of usescases within the media analytics segment that we’re targeting with ATS-M First : IOT and Video Analytics where video is coming in directly from a camera into the network and being processed to gather information. These typically object detection, object classification, and segmentation algorithms Next: These algorithms are used “Library Indexing and Compliance” category to really understand what is going in the video and extracting more information. Lastly is “AI Guided Enhancement” which is used to help improve video quality or drive down the cost of transmitting the video. Here is what we are doing on ATS-M: One: Intel is optimizing the most popular AI frameworks with TensorFlow, pytorch, and openvino to work efficiently with ATS-M on visual inference models. Two: You can use the same tools in the openvino tool suite to enable hybrid workflows between CPUs and GPUs Three: In addition to AV1, ATS-M will continue to support multiple video CODECs