| System configurations | Model 8247-42L |
|---|---|
| Processor and Memory | |
| Microprocessors (with GPU installed) | Two 10-core 3.42 GHz POWER8 processor cards or Two 12-core 3.02 GHz POWER8 processor cards |
| Microprocessors (available when no GPU installed and run on PowerVM) | One or Two 8-core 4.15 GHz POWER8 processor cards or Two 12-core 3.52 GHz POWER8 processor cards |
| Level 2 (L2) cache | 512 KB L2 cache per core |
| Level 3 (L3) cache | 8 MB L3 cache per core |
| Level 4 (L4) cache | 16 MB per DIMM |
| Memory Min/Max | 16 GB, 32 GB, 64 GB and 128 GB 1600 MHz DDR3 module, 32 GB to 2 TB |
| Processor-to-memory bandwidth | 192 GBps per socket |
| Storage and I/O | |
| Standard backplane | 12 small form factor (SFF) bays for Hard Disk Drive (HDD) |
| With dual IOA higher function backplane (available when no GPU installed and run on PowerVM) | 18 SFF bays for HDD/SSD plus 8 1.8-inch bays for SSD |
| Media bays | One slim line DVD |
| Integrated SAS Controller | Standard RAID 0, 5, 6,10 |
| Adapter slots | Included one x8 PCIe slots must contain a 1 Gb Ethernet LAN available for client use Eleven PCIe Gen3 slots: four x16 plus seven PCIe Gen3 x 8 Up to Two NVIDIA adapters available Two CAPI adapters per processor module |
| I/O Bandwidth | 96 GBps per socket |
| Expansion features (Optional) | |
| Max PCIe Gen3 I/O drawer (available when no GPU installed and run on PowerVM) |
2 |
| Power, RAS, system software and physical characteristics and warranty | |
| Power supply | 100 V to 240 V |
| RAS features | Processor instruction retry Chip kill memory ECC L2 cache, L3 cache Service processor with fault monitoring Hot-swappable disk bays Hot-plug and redundant power supplies and cooling fans Dynamic processor deallocation Extended error handling on PCI slots |
| Operating systems | Linux on POWER®* |
| System dimensions | 427.5 W x 173 H x 750.5 D mm |
IBM Power System S824L
- Revolutionize IT with the first server to leverage OpenPOWER Foundation technology to dramatically accelerate Java, big data and technical computing applications
- Offload highly parallel operations to a GPU accelerator and boost workload performance
- Help realize competitive advantages at a lower cost
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