LEGaTO Heterogeneous Hardware
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The LEGaTO project received funding from the EU's Horizon 2020 program to develop a heterogeneous hardware platform called RECS for cloud to edge computing. RECS uses a modular microserver approach integrating CPUs, GPUs, FPGAs, and SOCs. It allows for flexible node composition through virtual functions to enable different compute and communication topologies.
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LEGaTO Heterogeneous Hardware
- 1. The LEGaTO project has received funding from the European Union's Horizon 2020 research and innovation programme under the grant agreement No 780681 16.10.20 LEGaTO Heterogeneous Hardware LEGaTO thematic session – HiPEAC CSW Autumn 2020 Jens Hagemeyer Bielefeld University
- 2. Computer Systems Week LEGaTO Toolchain
- 3. Computer Systems Week Heterogeneous hardware Data Centers’ Challenges • Performance • Costs (TCO) x86 GPU FPGA ARM v8 GPU SoC FPGA SoC Developers’ Challenge • Select optimal target architecture • Parallel processing & orchestration RECS RECS - Resource Efficient Cluster Server vs. LEGaTO Cloud to Edge Microserver Platform
- 4. Computer Systems Week LEGaTO Cloud to Edge platform Edge Computing Cloud Computing Low Latency Computing Driven #Sites > 1M > 10K 100-10K < 100 Footprint Embedded Small (1RU) Medium (2RU) Large (3RU) Power Budget < 10W < 500W 500W – 2KW > 2KW t.RECS RECS|Box Durin RECS|Box Deneb Embedded Computing Microserver module # Microserver - up to 3 up to 48 up to 144
- 5. Computer Systems Week RECS Architecture Overview High-Performance Carrier (up to 3 Microservers) Low-Power Carrier (up to 16 Microservers) RECS Server “Deneb” • Heterogeneous microserver approach, integrating CPU, GPU and FPGA technology • High-speed, low latency communication infrastructure, enabling accelerators, scalable across multiple servers • Modular, blade-style design, hot pluggable/swappable
- 6. Computer Systems Week RECS|Box Cloud Server RECS (up to 15 Carriers) Carrier (PCIe Expansion)Carrier (High Performance) e.g. GPU-Accelerator Carrier (Low Power) #3 #2 Microserver (High Performance) #1 Microserver (Low Power) #16 #3 #2 Microserver (Low Power) #1 High-Speed Low-Latency Network (PCIe, High-Speed Serial) Compute Network (up to 40 GbE) Management Network (KVM, Monitoring, …) HDMI/USB iPass+ HD QSFP+ RJ45 Ext. Connectors GPU SoCFPGA SoC ARM Soc Low-Power Microserver (Apalis/Jetson) x86 ARM v8 High-Performance Microserver (COM Express/ COM-HPC) FPGA SoC High-Performance Carrier (up to 3 Microservers) Low-Power Carrier (up to 16 Microservers) RECS Server “Deneb”
- 7. Computer Systems Week RECS Microserver Overview Xilinx FPGAs Intel FPGAs Low-Power Microserver High-Performance Microserver CPU Microserver FPGA MicroserverGPGPU NVIDIA Jetson TX1/TX2 4 Core A57@1.73 GHz + Maxwell GPGPU@1.5 GHz 2 Core Denver + 4 Core A57 + Pascal GPGPU@1.5 GHz ARMv8 Server SoC 32 Core A72@2.4 GHz NVIDIA Tesla P100/V100 Pascal/Volta GPGPU@1.3 GHz Intel Stratix 10 SoC 2,800 kLE Xilinx Zynq 7020 85 kLC PCIe-Extensions PCIe SSD Xeon Phi RAPTOR FPGA acc.
- 8. Computer Systems Week t.RECS Edge Server • Optimized platform for local / edge applications • Provide interfaces for − Video − Camera − Peripheral input (USB) • Compact dimensions (1RU) • Combine FPGA and GPU acceleration t.RECS Edge Server MicroserverMicroserver Microserver Switched PCIe (Host to Host) Externalinterfaces PCIeexpansion Ethernet (up to 10 GbE) Management Network (KVM, Monitoring, …) Smart Mirror use case I/O (Camera, Display, Radar/Lidar, Audio)
- 9. Computer Systems Week t.RECS Microserver – COM-HPC • Large, open consortium • Currently in finalization stage • Driven by industry requirements
- 10. Computer Systems Week Node composition - Introduction • Node Composition enables software defined computing x86 FPGA x86 x86 x86 x86 x86 NVMe SSD GPU GPU GPU GPU GPU GPU FPGA FPGA FPGA FPGA FPGA NVMe SSD NVMe SSD NVMe SSD ARM ARM ARM ARM ARM ARM NVMe SSD is shared via Virtual Functions
- 11. Computer Systems Week Node composition - Basics • Scenario: x86 Node and PCIe Peripheral • Scenario: FPGA Topologies (direct high-speed serial links) x86 node PCIe Extension card FPGA FPGA FPGA FPGA x2x2 x2 x2 x2x2 FPGA FPGA FPGA FPGA x4x4 x4 x4 x16 ● ● ● ● ● ● dynamic reconfiguration
- 12. Computer Systems Week Node composition – Virtual functions PCIe Network Controller Virtual Network Function Virtual Network Function Virtual Network Function Virtual Network Function Virtual Network Function VM 1 VM 2 ● ● ● ● ● ● • PCIe devices can provide Virtual Functions • Common use-case: Network controller on virtualization host • Controller provides Virtual Functions (like virtual network cards) • Virtual Functions can be used by Virtual Machines • Frees hypervisor from I/O handling
- 13. Computer Systems Week Node composition - Example x86 node x8 Virtual DMA Function x8 x4 • PCIe switch shares Virtual Storage Functions (provided by NVMe SSD) • PCIe switch offers Virtual DMA Functions • x86 nodes and FPGA use Virtual Storage and DMA Functions • Direct high-speed low latency link between x86 node and FPGA x86 node Virtual DMA Functionx8 NVMe PCIe SSD FPGA Virtual Storage Function Virtual Storage Function x4 Virtual Storage Function PCIe Switch Virtual Storage Function
- 14. Computer Systems Week Node composition - Benchmarking • Improved latency (4x), compared to 10G ETH • Up to 54 Gbit/s interconnect, depending on buffer/window size • Support two different modes − Virtual NIC: Can be used like an Ethernet device − RDMA: Can be used via MPI/Verbs
- 15. Computer Systems Week Node composition - Management • Central Application/Runtime resource management • Embedded RECS_Master management software • Backend Driver (Redfish API) • Resource Inventory • Power Control • Node Composition • Dynamic Reconfiguration • Frontend (Web UI) • Resource Inventory • Power Control • Node Composition • Network Configuration • Monitoring Resource Inventory Power Control Node Composition Dynamic Reconfiguration Web UI Application Administrator Application Runtime Redfish API RECS_Master Resource Inventory Power Control Node Composition Network Configuration Monitoring
- 16. Computer Systems Week Hardware Summary • Flexible Cloud to Edge approach, covers IoT as well as HPC • Heterogeneous microserver approach, integrating CPU, GPU and FPGA technology • Supports latest COM-HPC microserver technology • Node composition enables flexible compute and communication topologies