BAM! NVIDIA And IBM Partner To Let GPUs Talk Directly To SSDs For A Major Performance Lift

If you're reading this, you probably don't need us to explain that CPUs are very good at doing one thing after another, while GPUs are very good at doing a whole lot of the same thing at once. They're radically different design paradigms, and a computer usually performs best, at least currently,  when it has both working in tandem.

The thing is, despite their differences, the essential function of both is to take input data and compute on it for output. In a typical system, storage I/O is connected to the CPU and the GPU is treated as a co-processor or sub-processor; when the GPU needs data, it has to get it from the CPU first. That's not really a problem per se, except that in some modern systems the GPU is doing much more work than the CPU is. Ultimately, in that case, using the CPU to orchestrate everything collectively can reduce the performance of both processors.


Well, nowhere is the GPU dominant over the CPU like in supercomputing servers, where the "accelerators" (in many cases GPUs) do the overwhelming majority of the work. Naturally NVIDIA, who makes most of its money selling these accelerators, has quite an interest in accelerating GPU I/O throughput as well. Team Green, in collaboration with Big Blue as well as some folks from Stanford and the University of Buffalo, seem to have come up with another method for solving this problem, and they've given it a wonderfully-evocative name: BAM. However, the technology isn't quite a nod to Emril Lagasse, as you might expect.

BAM, stylized also as BaM, stands for "Big Accelerator Memory." Put simply, it's a software-based approach to move things that would normally be done on the CPU to GPU cores. This allows the "accelerators" in servers and HPC systems to snatch data directly from RAM and SSD storage without needing the CPU's approval first, thus speeding up access dramatically and lowering overhead.