Gọi NgayThông số kĩ thuật
| CUDA PARALLEL PROCESSING CORES | 2 x 1536 |
| INTERFACE | 320-bit |
| FRAME BUFFER MEMORY | 8 GB GDDR5 |
| MEMORY BANDWIDTH | 320 GBytes/sec |
| DISPLAY CONNECTORS | None |
| MAX POWER CONSUMPTION | 225 W |
| INTERNAL CONNECTORS AND HEADERS | (1) 6-pin PCI Express power connector (1) 8-pin PCI Express power connector |
| GRAPHICS BUS | PCI Express 2.0 x16 |
| FORM FACTOR | 110 mm (H) x 265 mm (L) – Dual Slot |
| THERMAL SOLUTION | Passive |
| Peak double precision floating point performance (board) | 0.19 teraflops |
| Peak single precision floating point performance (board) | 4.58 teraflops |
| Number of GPUs | 2 x GK104s |
| GPU computing applications | Seismic, Image Signal processing Video analytics |
| Architecture features | SMX |
| System | Servers only |
| TESLA K10 – GPU Computing Accelerator Common Features | |
| ECC Memory Error Protection | Meets a critical requirement for computing accuracy and reliability in datacenters and supercomputing centers. External DRAM is ECC protected in Tesla K10 and both external and internal memories are ECC protected in Tesla K20X. |
| System Monitoring Features | Integrates the GPU subsystem with the host system’s monitoring and management capabilities such as IPMI or OEM-proprietary tools. IT staff can thus manage the GPU processors in the computing system using widely used cluster/grid management solutions. |
| L1 and L2 caches | Accelerates algorithms such as physics solvers, ray-tracing, and sparse matrix multiplication where data addresses are not known beforehand |
| Asynchronous Transfer with dual DMA engines | Turbocharges system performance by transferring data over the PCIe bus while the computing cores are crunching other data. |
| Flexible programming environment with broad support of programming languages and APIs | Choose OpenACC, CUDA toolkits for C, C++, or Fortran to express application parallelism and take advantage of the innovative Kepler architecture. |
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