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To use this tool, you must specify
A basic block is a linear section of code with one entry point and one exit point. A basic block vector (BBV) is a list of all basic blocks entered during program execution, and a count of how many times each basic block was run.
BBV is a tool that generates basic block vectors for use with the SimPoint analysis tool. The SimPoint methodology enables speeding up architectural simulations by only running a small portion of a program and then extrapolating total behavior from this small portion. Most programs exhibit phase-based behavior, which means that at various times during execution a program will encounter intervals of time where the code behaves similarly to a previous interval. If you can detect these intervals and group them together, an approximation of the total program behavior can be obtained by only simulating a bare minimum number of intervals, and then scaling the results.
In computer architecture research, running a benchmark on a cycle-accurate simulator can cause slowdowns on the order of 1000 times, making it take days, weeks, or even longer to run full benchmarks. By utilizing SimPoint this can be reduced significantly, usually by 90-95%, while still retaining reasonable accuracy.
A more complete introduction to how SimPoint works can be found in the paper "Automatically Characterizing Large Scale Program Behavior" by T. Sherwood, E. Perelman, G. Hamerly, and B. Calder.
To quickly create a basic block vector file, you will call Valgrind like this:
valgrind --tool=exp-bbv /bin/ls
In this case we are running on
To create actual SimPoint results, you will need the SimPoint utility, available from the SimPoint webpage. Assuming you have downloaded SimPoint 3.2 and compiled it, create SimPoint results with a command like the following:
./SimPoint.3.2/bin/simpoint -inputVectorsGzipped \ -loadFVFile bb.out.1234.gz \ -k 5 -saveSimpoints results.simpts \ -saveSimpointWeights results.weights
where bb.out.1234.gz is your compressed basic block vector file generated by BBV.
The SimPoint utility does random linear projection using 15-dimensions, then does k-mean clustering to calculate which intervals are of interest. In this example we specify 5 intervals with the -k 5 option.
The outputs from the SimPoint run are the
BBV-specific command-line options are:
The Basic Block Vector is dumped at fixed intervals. This
is commonly done every 100 million instructions; the
The output file looks like this:
T:45:1024 :189:99343 T:11:78573 :15:1353 :56:1 T:18:45 :12:135353 :56:78 314:4324263
Each new interval starts with a T. This is followed on the same line by a series of basic block and frequency pairs, one for each basic block that was entered during the interval. The format for each block/frequency pair is a colon, followed by a number that uniquely identifies the basic block, another colon, and then the frequency (which is the number of times the block was entered, multiplied by the number of instructions in the block). The pairs are separated from each other by a space.
The frequency count is multiplied by the number of instructions that are in the basic block, in order to weigh the count so that instructions in small basic blocks aren't counted as more important than instructions in large basic blocks.
The SimPoint program only processes lines that start with a "T". All other lines are ignored. Traditionally comments are indicated by starting a line with a "#" character. Some other BBV generation tools, such as PinPoints, generate lines beginning with letters other than "T" to indicate more information about the program being run. We do not generate these, as the SimPoint utility ignores them.
Valgrind provides all of the information necessary to create BBV files. In the current implementation, all instructions are instrumented. This is slower (by approximately a factor of two) than a method that instruments at the basic block level, but there are some complications (especially with rep prefix detection) that make that method more difficult.
Valgrind actually provides instrumentation at a superblock level.
A superblock has one entry point but unlike basic blocks can
have multiple exit points. Once a branch occurs into the middle
of a block, it is split into a new basic block. Because
Valgrind cannot produce "true" basic blocks, the generated
BBV vectors will be different than those generated by other tools.
In practice this does not seem to affect the accuracy of the
SimPoint results. We do internally force the
When a superblock is run for the first time, it is instrumented with our BBV routine. A block info (bbInfo) structure is allocated which holds the various information and statistics for the block. A unique block ID is assigned to the block, and then the structure is placed into an ordered set. Then each native instruction in the block is instrumented to call an instruction counting routine with a pointer to the block info structure as an argument.
At run-time, our instruction counting routines are called once per native instruction. The relevant block info structure is accessed and the block count and total instruction count is updated. If the total instruction count overflows the interval size then we walk the ordered set, writing out the statistics for any block that was accessed in the interval, then resetting the block counters to zero.
On the x86 and amd64 architectures the counting code has extra code to handle rep-prefixed string instructions. This is because actual hardware counts a rep-prefixed instruction as one instruction, while a naive Valgrind implementation would count it as many (possibly hundreds, thousands or even millions) of instructions. We handle rep-prefixed instructions specially, in order to make the results match those obtained with hardware performance counters.
BBV also counts the fldcw instruction. This instruction is used on x86 machines in various ways; it is most commonly found when converting floating point values into integers. On Pentium 4 systems the retired instruction performance counter counts this instruction as two instructions (all other known processors only count it as one). This can affect results when using SimPoint on Pentium 4 systems. We provide the fldcw count so that users can evaluate whether it will impact their results enough to avoid using Pentium 4 machines for their experiments. It would be possible to add an option to this tool that mimics the double-counting so that the generated BBV files would be usable for experiments using hardware performance counters on Pentium 4 systems.
BBV supports threaded programs. When a program has multiple threads, an additional basic block vector file is created for each thread (each additional file is the specified filename with the thread number appended at the end).
There is no official method of using SimPoint with threaded workloads. The most common method is to run SimPoint on each thread's results independently, and use some method of deterministic execution to try to match the original workload. This should be possible with the current BBV.
BBV has been tested on x86, amd64, and ppc32 platforms. An earlier version of BBV was tested in detail using hardware performance counters, this work is described in a paper from the HiPEAC'08 conference, "Using Dynamic Binary Instrumentation to Generate Multi-Platform SimPoints: Methodology and Accuracy" by V.M. Weaver and S.A. McKee.
Using this program slows down execution by roughly a factor of 40 over native execution. This varies depending on the machine used and the benchmark being run. On the SPEC CPU 2000 benchmarks running on a 3.4GHz Pentium D processor, the slowdown ranges from 24x (mcf) to 340x (vortex.2).
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