How the SPARC T4 Processor Optimizes Throughput Capacity: A Case Study

This white paper demonstrates the architected latency hiding features of Oracle’s UltraSPARC T2+ and SPARC T4 processors

That is the first sentence from this technical white paper, but what does it exactly mean?

Let's consider a very simple example, the computation of a = b + c. This boils down to the following (pseudo-assembler) instructions that need to be executed:

      load  @b, r1
      load  @c, r2
      add   r1,r2,r3
      store r3, @a

The first two instructions load variables b and c from an address in memory (here symbolized by @b and @c respectively). These values go into registers r1 and r2. The third instruction adds the values in r1 and r2. The result goes into register r3. The fourth instruction stores the contents of r3 into the memory address symbolized by @a.

If we're lucky, both b and c are in a nearby cache and the load instructions only take a few processor cycles to execute. That is the good case, but what if b or c, or both, have to come from very far away? Perhaps both of them are in the main memory and then it easily takes hundreds of cycles for the values to arrive in the registers.

Meanwhile the processor is doing nothing and simply waits for the data to arrive. Actually, it does something. It burns cycles while waiting. That is a waste of time and energy. Why not use these cycles to execute instructions from another application or thread in case of a parallel program?

That is exactly what latency hiding on the SPARC T-Series processors does. It is a hardware feature totally transparent to the user and application. As soon as there is a delay in the execution, the hardware uses these otherwise idle cycles to execute instructions from another process. As a result, the throughput capacity of the system improves because idle cycles are no longer wasted and therefore more jobs can be run per unit of time.

This feature has been in the SPARC T-series from the beginning, so why this paper?

The difference with previous publications on this topic is in the amount of detail given. How this all works under the hood is fully explained using two example programs. Starting from the assembly language instructions, it is demonstrated in what way these programs execute. To really see what is happening we go down to the processor pipeline level, where the gaps in the execution are, and show in what way these idle cycles are filled by other copies of the same program running simultaneously.

Both the SPARC T4 as well as the older UltraSPARC T2+ processor are covered. You may wonder why the UltraSPARC T2+ is included. The focus of this work is on the SPARC T4 processor, but to explain the basic concept of latency hiding at this very low level, we start with the UltraSPARC T2+ processor because it is architecturally a much simpler design. From the single issue, in-order pipelines of this processor we then shift gears and cover how this all works on the much more advanced dual issue, out-of-order architecture of the T4.

The analysis and performance experiments have been conducted on both processors. The results depend on the processor, but in all cases the theoretical estimates are confirmed by the experiments.

If you're interested to read a lot more about this and find out how things really work under the hood, you can download a copy of the paper here.


A paper like this could not have been produced without the help of several other people.

I want to thank the co-author of this paper, Jared Smolens, for his very valuable contributions and our highly inspiring discussions. I'm also indebted to Thomas Nau (Ulm University, Germany), Shane Sigler and Mark Woodyard (both at Oracle) for their feedback on earlier versions of this paper. Karen Perkins (Perkins Technical Writing and Editing) and Rick Ramsey at Oracle were very helpful in providing editorial and publishing assistance.

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Ruud van der Pas is a Senior Staff Engineer in the Microelectronics organization at Oracle. His focus is on application performance, both for single threaded, as well as for multi-threaded programs. He is also co-author on the book Using OpenMP

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