4 ms·
I don't doubt that you have, although I would be curious about the mechanism. Spindles are spindles, whether they're feeding to a GPU or a CPU. I would be car
by fiatmoney 13y ago
I don't doubt that you have, although I would be curious about the mechanism. Spindles are spindles, whether they're feeding to a GPU or a CPU.
I would be careful about phrasing it as "memory bound is not an issue". There's a distinction between memory bandwidth (which GPUs excel at as long as the data is resident), memory latency (which GPUs are pretty bad at), and memory capacity. 12gb is slim in the grand scheme of things; my laptop has 16gb and you can get machines with >1TB of memory. Outside of the GPU's memory limits, you're relying on streaming data to/from the device, and potentially bound on PCIe bandwidth, or partitioning the problem across multiple GPUs/machines.
- Hydraulix989 13y agoRight. These problems are all addressable. We're using a streaming scheme to ensure that the bus bandwidth is fully utilized for each GPU. Moreover, a dispatcher will intelligently partition and distribute jobs across multiple hosts.
- tonydiv 13y agoCorrect. PCIe is the least of our concerns at 16GB/s. Some of our tests indicate that our GPU analyzes data at a rate of ~5GB/s. If we can feed it the data in that amount of time, we're in business. We're also parallelizing disk reads, which is one bottleneck at this point.