Wednesday, November 24, 2010

Happy Thanksgiving

While preparing your Thanksgiving meal, remember the following, dear readers.

Preserve fats

Happy Thanksgiving!

Saturday, November 20, 2010

B-Tree

Saturday morning algorithms practice: I implemented insert() and find() members std::map<> as a B-tree.

Each node in the B-tree has at most 2*t-1 keys and at most 2*t children. The best-case depth of a B-tree is log_{2*t}(N) and the worst case is log_{t}(N). During a search, O(2t) comparisons are performed per node, and O(height) nodes are visited.

For t = 3, my implementation shows the following complexity for searching:


N = 1000
Average nodes visited: 4.68
log_3(N) = 6.28771 (worst)
log_6(N) = 3.85529 (best)
tree depth = 5


For N = 25000, you may compare to an earlier implementation of skiplists.

N = 25000
Average nodes visited: 7.68968
log_3(N) = 9.21766 (worst)
log_6(N) = 5.65178 (best)
depth = 8

Wednesday, November 3, 2010

LLVM Floating-point Performance Bug

I've noticed an unusual behavior of the LLVM x86 code generator that results in
nearly a 4x slow-down in floating-point throughput that I would like to report.

I've written a compute-intensive microbenchmark to approach theoretical peak
throughput of the target processor by issuing a large number of independent
floating-point multiplies. The distance between dependent instructions is at
least four instructions to match the latency of the floating-point functional
unit in my Intel Core2 Quad (Q9550 at 2.83 GHz).

The microbenchmark itself replicates the following block 512 times:


.
.
{
p1 = p1 * a;
p2 = p2 * b;
p3 = p3 * c;
p4 = p4 * d;
}
.
.


Compiling with NVCC, Ocelot, and LLVM, I can confirm the interleaved instruction
schedule with a four-instruction reuse distance. An excerpt follows:


.
.
%r1500 = fmul float %r1496, %r24 ; compute %1500
%r1501 = fmul float %r1497, %r23
%r1502 = fmul float %r1498, %r22
%r1503 = fmul float %r1499, %r21

%r1504 = fmul float %r1500, %r24 ; first use of %1500
%r1505 = fmul float %r1501, %r23
%r1506 = fmul float %r1502, %r22
%r1507 = fmul float %r1503, %r21

%r1508 = fmul float %r1504, %r24 ; first use of %1504
.
.


The JIT compiler, however, seems to break the interleaving of independent instructions
and issues a long sequence of instructions with back-to-back dependencies. It is as if
all p1 = .. expressions are collected at once followed by all p2 = .. expressions and so
forth.

p1 = p1 * a
p1 = p1 * a
.
.

p2 = p2 * b
p2 = p2 * b
.
.

p3 = p3 * c
p3 = p3 * c
.
.


An actual excerpt of the generated x86 assembly follows:

mulss %xmm8, %xmm10
mulss %xmm8, %xmm10
.
. repeated 512 times
.

mulss %xmm7, %xmm9
mulss %xmm7, %xmm9
.
. repeated 512 times
.

mulss %xmm6, %xmm3
mulss %xmm6, %xmm3
.
. repeated 512 times
.


Since p1, p2, p3, and p4 are all independent, this reordering is correct. This would have
the possible advantage of reducing live ranges of values. However, in this microbenchmark,
the number of live values is eight single-precision floats - well within SSE's sixteen
architectural registers.

Moreover, the pipeline latency is four cycles meaning back-to-back instructions with true
dependencies cannot issue immediately. The benchmark was intentionally written to avoid this
hazard but LLVM's code generator seems to ignore that when it schedules instructions.

When I run this benchmark on my 2.83 GHz CPU [45.3 GFLOP/s stated single-precision throughput],
I observe the following performance results:

1 threads 0.648891 GFLOP/s
2 threads 1.489049 GFLOP/s
3 threads 2.209838 GFLOP/s
4 threads 2.940443 GFLOP/s


When I rewrite the generated assembly to exhibit the same interleaving as in the LLVM IR form

.
.
mulss %xmm8, %xmm10
mulss %xmm7, %xmm9
mulss %xmm6, %xmm3
mulss %xmm5, %xmm11

mulss %xmm8, %xmm10
mulss %xmm7, %xmm9
mulss %xmm6, %xmm3
mulss %xmm5, %xmm11

mulss %xmm8, %xmm10
mulss %xmm7, %xmm9
.
.


observed performance increases by nearly a factor of four:


1 threads 2.067118 GFLOP/s
2 threads 5.569419 GFLOP/s
3 threads 8.285519 GFLOP/s
4 threads 10.81742 GFLOP/s


I show similar results with packed single-precision floating point instructions. The LLVM-generated
machine code is nearly 4x slower than the interleaved schedule suggested by the LLVM IR input.


Vectorized - No instruction interleaving - back-to-back dependencies

1 threads 1.540621 GFLOP/s
2 threads 5.900833 GFLOP/s
3 threads 8.755953 GFLOP/s
4 threads 11.257122 GFLOP/s

Vectorized - Interleaved - stride-4 reuse distance

1 threads 3.157255 GFLOP/s
2 threads 22.104369 GFLOP/s
3 threads 32.300111 GFLOP/s
4 threads 39.112162 GFLOP/s


It is worth noting that 39.1 GFLOP/s is approaching the theoretical limits of the processor
(stated to be 45.25 GFLOP/s single-precision).