Sandy-Bridge CPU specification - cpu

I was able to put together bits here and there about the Sandy Bridge-E architecture but I am not totally sure about all the parameters e.g. the size of the L2 cache. Can anyone please confirm they are all correct? My main source was the 64-ia-32-architectures-optimization-manual.pdf

On sandy bridge, each core has 256KB of L2 (see the datasheet, section 1.1). for 6 cores, that's 1.5MB, but since each core only accesses its own, it's better to always look at it as 256KB per core.
Moreover, the peak gflops looks completely wrong. AVX is 16 flops/cycle (as single floats). with 6 cores, that's ~307 gflops/s at 3.2GHz.
Most of the rest of the data looks ok (looking at the datasheet and the specification of that model in particular), though I don't know for sure the associativity of each cache.

Related

Can all of L2/L3 cache be used by data? If so, why does the Graviton 3 bandwidth plot drop off after half the L2/L3 size, but only gradually?

Consider Graviton3, for example. It's a 64-core CPU with per-core caches 64KiB L1d and 1MiB L2. And a shared L3 of 64MiB across all cores. The RAM bandwidth per socket is 307GB/s (source).
In this plot (source),
we see that all-cores bandwidth drops off to roughly half, when the data exceeds 4MB. This makes sense: 64x 64KiB = 4 MiB is the size of the L1 data cache.
But why does the next cliff begin at 32MB? And why is the drop-off so gradual there? The private L2 caches of 64 cores is a total of 64 MiB, same as the shared L3 size.
It looks from the plot like they may not have tested any sizes between 32M and 64M. Looks like a straight line between those points on all 3 CPUs.
Since 64M is the total size of both L2 and L3, I'd expect a test like this to have slowed most of the way down at 64M. As Brendan says, page tables and a bit of code will take space, competing with the actual intended test data. If the benchmark loop is tight, stack won't come into play, except for interrupt handling.
Once you're evicting anything from a working set slightly larger than cache, you often evict almost everything before getting back to it, depending on pseudo-LRU luck. I'd expect a test size or 48 or even 56 MiB to be a lot closer to the 32 MiB data point than the 64 MiB data point.
Can all of L2/L3 cache be used by data?
In theory, yes; but only if there's no "non-data" (code) in the cache, only if you count "all data" (and don't just count a process' data and ignore things like stack and page tables), and only if there isn't any aliasing problems.
But why does the next cliff begin at 32MB? And why is the drop-off so gradual there?
For a fully associative cache I'd expect a sudden drop off at/near 32 MiB. However, large caches are almost never fully associative as it costs way to much to find anything in the cache.
As associativity decreases the chance of conflicts increases. For example, for an 8-way associative 64 MiB cache the pathological case is that everything conflicts and you're only able to effectively use 8 MiB of it.
More specifically, for a 64 MiB cache (with unknown associativity), and an "assumed Linux" environment that lacks support for cache coloring, it's reasonable to expect a smooth drop off that ends at 64 MiB.
Just to be clear, on a running Graviton 3 in AWS, an lscpu gives me 32MiB for L3 and not 64 MiB.
Caches (sum of all):
L1d: 4 MiB (64 instances)
L1i: 4 MiB (64 instances)
L2: 64 MiB (64 instances)
L3: 32 MiB (1 instance)
The original question is assuming an L3 of 64 MiB across all cores.
Blockquote
But why does the next cliff begin at 32MB? And why is the drop-off so gradual there? The private L2 caches of 64 cores is a total of 64 MiB, same as the shared L3 size.
Blockquote

Is the L1-Dcache the ultimate data cache and is DSB also a cache that can be simulated by gem5?

I wonder if the L1-Dcache is the ultimate cache that data comes from. Because I know for i-cache, there is a DSB which is even closer to CPU which could be seen as L0-icache.
Also, I am interested in what hardware changes could influence DSB's performance? I mean for cache, there are things such as cache size, Cache Associativity. But is DSB also just a cache that can be influenced by those factors?
If yes, can I simulate the results using gem5. I know with gem5, I can configure the L1 instruction cache and observe L1 instruction cache performance. How could same things be done for DSB on gem?
I wonder if the L1-Dcache is the ultimate cache that data comes from
Yes, or the store buffer. Globally Invisible load instructions explains how partial store-forwarding can let a core load a dword value that was never globally visible, so no other core could have loaded.
The DSB (uop cache) is a cache, but it doesn't cache machine code. It caches the result of decoding x86 machine code into uops.
It has various limitations like not using more than 3 "lines" for uops from the same 32-byte block of x86 machine code, so modeling is it not as simple as just size / assocativity. e.g. each way (aka line) can hold up to 6 uops, but ends with an unconditional (or predicted-taken) branch uop. And all the uops from a multi-uop instruction have to go in the same line.
The number of fused-domain uops from each x86 instruction depend on exactly what instruction it is; see https://uops.info/, but note that un-lamination will mean some instructions take more uops in the issue/rename stage and ROB than they do decoders and uop-cache. (Micro fusion and addressing modes)
Agner Fog's microarch guide has some detailed testing results (https://agner.org/optimize/), and see also https://www.realworldtech.com/sandy-bridge/4/
The basic parameters of Intel's uop cache are, as described in the Sandybridge section Agner's microarch guide:
The µop cache is organized as 32 sets x 8 ways x 6 µops, totaling a maximum capacity of
1536 µops. It can allocate a maximum of 3 lines of 6 µops each for each aligned and
contiguous 32-bytes block of code.
AFAIK, this geometry has remained unchanged from SnB through Skylake and Ice Lake.
The L1i cache is inclusive of the uop cache. The uop cache is virtually-addressed, so TLB lookups aren't needed. But it has to be evicted on TLB invalidation as well, I guess. (That's not a huge problem because the legacy decoders are quite good; Sandybridge-family avoided problems of P4's slow decoding, and trying to use its trace cache instead of a normal L1i.)
Note that AMD's Zen microarchitecture family also uses a uop cache. They don't call it a DSB, and it presumably has some differences from Intel's.
Also, I am interested in what hardware changes could influence DSB's performance?
Skylake increased the bandwidth of uop-cache -> IDQ from 4 to 6 uops per cycle. So even in high-throughput code, the uop-cache can "catch up" after bubbles partially drain the IDQ.
It can still only read 1 uop cache line per cycle, though, so for example on a Skylake where microcode updates disabled the loop buffer (LSD), a tiny loop that would normally run at 1 cycle per iteration can slow down to 2 cycles if the loop is split across a 32-byte boundary, because that means its uops will be in 2 separate uop-cache lines. (Like 1 or 2 from each line.)
But Haswell can sustain 4 uops per clock from the uop cache under ideal conditions, even with instructions that fully pack uop cache lines with 6 uops per line. So there's apparently some buffering between uop cache-line fetch and adding to the IDQ, otherwise it would be a 4 : 2 pattern if all the uops added to the IDQ had to come from the same line.

How can x86 bsr/bsf have fixed latency, not data dependent? Doesn't it loop over bits like the pseudocode shows?

I am on the hook to analyze some "timing channels" of some x86 binary code. I am posting one question to comprehend the bsf/bsr opcodes.
So high-levelly, these two opcodes can be modeled as a "loop", which counts the leading and trailing zeros of a given operand. The x86 manual has a good formalization of these opcodes, something like the following:
IF SRC = 0
THEN
ZF ← 1;
DEST is undefined;
ELSE
ZF ← 0;
temp ← OperandSize – 1;
WHILE Bit(SRC, temp) = 0
DO
temp ← temp - 1;
OD;
DEST ← temp;
FI;
But to my suprise, bsf/bsr instructions seem to have fixed cpu cycles. According to some documents I found here: https://gmplib.org/~tege/x86-timing.pdf, seems that they always take 8 CPU cycles to finish.
So here are my questions:
I am confirming that these instructions have fixed cpu cycles. In other words, no matter what operand is given, they always take the same amount of time to process, and there is no "timing channel" behind. I cannot find corresponding specifications in Intel's official documents.
Then why it is possible? Apparently this is a "loop" or somewhat, at least high-levelly. What is the design decision behind? Easier for CPU pipelines?
BSF/BSR performance is not data dependent on any modern CPUs. See https://agner.org/optimize/, https://uops.info/, or http://instlatx64.atw.hu/ for experimental timing results, as well as the https://gmplib.org/~tege/x86-timing.pdf you found.
On modern Intel, they decode to 1 uop with 3 cycle latency and 1/clock throughput, running only on port 1. Ryzen also runs them with 3c latency for BSF, 4c latency for BSR, but multiple uops. Earlier AMD is sometimes even slower.
(Prefer rep bsf aka tzcnt in code that might run on AMD CPUs, if you don't need the FLAGS difference between bsf and tzcnt for zero inputs. lzcnt and tzcnt are fast on AMD as well, like 1 cycle latency with 3/clock throughput for lzcnt on Zen 2 (https://uops.info/). Unfortunately lzcnt and bsr aren't compatible that way, so you can't use it in an "optimistic" forward-compatible way, you have to know which you're getting.)
Your "8 cycle" (latency and throughput) cost appears to be for 32-bit BSF on AMD K8, from Granlund's table that you linked. Agner Fog's table agrees, (and shows it decodes to 21 uops instead of having a dedicated bit-scan execution unit. But the microcoded implementation is presumably still branchless and not data-dependent). No clue why you picked that number; K8 doesn't have SMT / Hyperthreading so the opportunity for an ALU-timing side channel is much reduced.
Do note that they have an output dependency on the destination register, which they leave unmodified if the input was zero. AMD documents this behaviour, Intel implements it in hardware but documents it as an "undefined" result, so unfortunately compilers won't take advantage of it and human programmers maybe should be cautious. IDK if some ancient 32-bit only CPU had different behaviour, or if Intel is planning to ever change (doubtful!), but I wish Intel would document the behaviour at least for 64-bit mode (which excludes any older CPUs).
lzcnt/tzcnt and popcnt on Intel CPUs (but not AMD) have the same output dependency before Skylake and before Cannon Lake (respectively), even though architecturally the result is well-defined for all inputs. They all use the same execution unit. (How is POPCNT implemented in hardware?). AMD Bulldozer/Ryzen builds their bit-scan execution unit without the output dependency baked in, so BSF/BSR are slower than LZCNT/TZCNT (multiple uops to handle the input=0 case, and probably also setting ZF according to the input, not the result).
(Taking advantage of that with intrinsics isn't possible; not even with MSVC's _BitScanReverse64 which uses a by-reference output arg that you could set first. MSVC doesn't respect the previous value and assumes it's output-only. VS: unexpected optimization behavior with _BitScanReverse64 intrinsic)
The pseudocode in the manual is not the implementation
(i.e. it's not necessarily how hardware or microcode works).
It gives precisely the same result in all cases, so you can use it to understand exactly what will happen for any corner cases the text leaves you wondering about. That is all.
The point is to be simple and easy to understand, and that means modeling things in terms of simple 2-input operations which happen serially. C / Fortran / typical pseudocode doesn't have operators for many-input AND, OR, or XOR, but you can build that in hardware up to a point (limited by fan-in, the opposite of fan-out).
Integer addition can be modelled as bit-serial ripple carry, but that's not how it's implemented! Instead, we get single-cycle latency for 64-bit addition with far fewer than 64 gate delays using tricks like carry lookahead adders.
The actual implementation techniques used in Intel's bit-scan / popcnt execution unit are described in US Patent US8214414 B2.
Abstract
A merged datapath for PopCount and BitScan is described. A hardware
circuit includes a compressor tree utilized for a PopCount function,
which is reused by a BitScan function (e.g., bit scan forward (BSF) or
bit scan reverse (BSR)).
Selector logic enables the compressor tree to
operate on an input word for the PopCount or BitScan operation, based
on a microprocessor instruction. The input word is encoded if a
BitScan operation is selected.
The compressor tree receives the input
word, operates on the bits as though all bits have same level of
significance (e.g., for an N-bit input word, the input word is treated
as N one-bit inputs). The result of the compressor tree circuit is a
binary value representing a number related to the operation performed
(the number of set bits for PopCount, or the bit position of the first
set bit encountered by scanning the input word).
It's fairly safe to assume that Intel's actual silicon works similarly to this. Other Intel patents for things like out-of-order machinery (ROB, RS) do tend to match up with performance experiments we can perform.
AMD may do something different, but regardless we know from performance experiments that it's not data-dependent.
It's well known that fixed latency is a hugely beneficial thing for out-of-order scheduling, so it's very surprising when instructions don't have fixed latency. Sandybridge even went so far as to standardize uop latencies to simplify the scheduler and reduce the opportunities write-back conflicts. (e.g. a 3-cycle latency uop followed by a 2-cycle latency uop to the same port would produce 2 results in the same cycle). This meant making complex-LEA (with all 3 components: [disp + base + idx*scale]) take 3 cycles instead of just 2 for the 2 additions like on previous CPUs. There are no 2-cycle latency uops on Sandybridge-family. (There are some 2-cycle latency instructions, because they decode to 2 uops with 1c latency each. The scheduler schedules uops, not instructions).
One of the few exceptions to the rule of fixed latency for ALU uops is division / sqrt, which uses a not-fully-pipelined execution unit. Division is inherently iterative, unlike multiplication where you can make wide hardware that does the partial products and partial additions in parallel.
On Intel CPUs, variable-latency for L1d cache access can produce replays of dependent uops if the data wasn't ready when the scheduler optimistically hoped it would be.
Is there a penalty when base+offset is in a different page than the base?
Why does the number of uops per iteration increase with the stride of streaming loads?
Weird performance effects from nearby dependent stores in a pointer-chasing loop on IvyBridge. Adding an extra load speeds it up?
The 80x86 manual has a good description of the expected behavior, but that has nothing to do with how it's actually implemented in silicon in any model from any manufacturer.
Let's say that there's been 50 different CPU designs from Intel, 25 CPU designs from AMD, then 25 more from other manufacturers (VIA, Cyrix, SiS/Vortex, NSC, ...). Out of those 100 different CPU designs, maybe there's 20 completely different ways that BSF has been implemented, and maybe 10 of them have fixed timing, 5 have timing that depends on every bit of the source operand, and 5 depend on groups of bits of the source operand (e.g. maybe like "if highest 32 bits of 64-bit operand are zeros { switch to 32-bit logic that's 2 cycles faster }").
I am confirming that these instructions have fixed cpu cycles. In other words, no matter what operand is given, they always take the same amount of time to process, and there is no "timing channel" behind. I cannot find corresponding specifications in Intel's official documents.
You can't. More specifically, you can test or research existing CPUs, but that's a waste of time because next week Intel (or AMD or VIA or someone else) can release a new CPU that has completely different timing.
As soon as you rely on "measured from existing CPUs" you're doing it wrong. You have to rely on "architectural guarantees" that apply to all future CPUs. There is no "architectural guarantee". You have to assume that there may be a timing side-channel (even if there isn't for current CPUs)
Then why it is possible? Apparently this is a "loop" or somewhat, at least high-levelly. What is the design decision behind? Easier for CPU pipelines?
Instead of doing a 64-bit BSF, why not split it into a pair of 32-bit pieces and do them in parallel, then merge the results? Why not split it into eight 8-bit pieces? Why not use a table lookup for each 8-bit piece?
The answers posted have explained well that the implementation is different from pseudocode. But if you are still curious why the latency is fixed and not data dependent or uses any loops for that matter, you need to see electronic side of things.
One way you could implement this feature in hardware is by using a Priority encoder.
A priority encoder will accept n input lines that can be one or off (0 or 1) and give out the index of the highest priority line that is on. Below is a table from the linked Wikipedia article modified for a most significant set bit function.
input | output index of first set bit
0000 | xx undefined
0001 | 00 0
001x | 01 1
01xx | 10 2
1xxx | 11 3
x denotes the bit value does not matter and can be anything
If you see the circuit diagram on the article, there are no loops of any kind, it is all parallel.

Store forwarding Address vs Data: What the difference between STD and STA in the Intel Optimization guide?

I'm wondering if any Intel experts out there can tell me the difference between STD and STA with respect to the Intel Skylake core.
In the Intel optimization guide, there's a picture describing the "super-scalar ports" of the Intel Cores.
Here's the PDF. The picture is on page 40.
.
Here's another picture from page 78, this picture describes "Store Address" and "Store Data":
Prepares the store forwarding and store retirement logic with the address of the data being stored.
Prepares the store forwarding and store retirement logic with the data being stored.
Considering that Skylake can perform #1 3x per clock cycle, but can only perform #2 once per clock cycle, I was curious what the difference was between these two.
It seems "natural" to me that store-forwarding would be done to the address of the data. But I can't understand when store-forwarding on the data (aka: STD / Port 4) would ever be done. Are there any assembly / optimization experts out there that can help me understand exactly the difference between STD and STA is?
Intel CPUs have been splitting stores into store-address and store-data since the first P6-family microarchitecture, Pentium Pro.
But store-address and store-data uops can micro-fuse into one fused-domain uop. On Sandy/IvyBridge, indexed addressing modes are un-laminated as described in Intel's optimization manual. But Haswell and later can keep them micro-fused even in the ROB, so they aren't un-laminated. See Micro fusion and addressing modes. (Intel doesn't mention this, and Agner Fog hasn't had time to test extensively for Haswell/Skylake so his usually-good microarch PDF doesn't even mention un-lamination at all. But you should still definitely read it to learn more about how uops work and how instructions are decoded and go through the pipeline. See also other x86 performance links in the x86 tag wiki)
Considering that Skylake can perform #1 3x per clock cycle, but can only perform #2 once per clock cycle
Ports 2 and 3 can also run load uops on their AGUs, leaving the load-data part of the port unused that cycle. Port7 only has a dedicated store-AGU for simple addressing modes.
Store addressing modes with an index register can't use port 7, only p2/p3. But if you do use "simple" addressing modes for stores, the peak throughput is 2 loads + 1 store per clock.
On Nehalem and earlier (P6 family), p2 was the only load port, p3 was the store-address port, and p4 was store-data.
On IvyBridge/Sandybridge, there weren't separate ports for store-address uops, they always just ran on the AGU (Address Generation Unit) in the load ports (p23). With 256b loads / stores, the AGU was only needed every other cycle (256b load or store uops occupy the load or store-data ports for 2 cycles, but the load ports can accept a store-address uop during that 2nd cycle). So 2 load / 1 store per clock was in theory sustainable on Sandybridge, but only if most of it was with AVX 256-bit vector loads / stores running as two 128-bit halves.
Haswell added the dedicated store-AGU on port7 and widened the load/store execution units to 256b, because there aren't spare cycles when the load ports don't need their AGUs if there's a steady supply of loads.
A store-address uop writes the address (and width, I guess) into the store buffer (aka Memory Order Buffer in Intel's terminology). Having this happen separately, and possibly before the data to be stored is even ready lets later loads (in program order) detect whether they overlap the store or not.
Out-of-order execution of loads when there are pending stores with unknown address is problematic: a wrong guess means having to roll back the pipeline. (I think the machine_clears.memory_ordering perf counter event includes this. It is possible to get non-zero counts for this from single-threaded code, but I forget if I had definite evidence that Skylake sometimes speculatively guesses that loads don't overlap unknown-address stores).
As David Kanter points out in his Haswell microarch writeup, a load uop also needs to probe the store buffer to check for forwarding / conflicts, so an execution unit that only runs store-address uops is cheaper to build.
Anyway, I'm not sure what the performance implications would be if Intel redesigned things so port7 had a full AGU that could handle indexed addressing modes, too, and made store-address uops only run on p7, not p2/p3.
That would stop store-address uops from "stealing" p23, which does happen and which reduces max sustained L1D bandwidth from 96 bytes / cycle (2 load + 1 store of 32-byte YMM vectors) down to ~81 bytes / cycle for Skylake according to a table in Intel's optimization manual. But under the right circumstances, Skylake can sustain 2 loads + 1 store per clock of 4-byte operands, so maybe that 81-byte / cycle number is limited by some other microarchitectural limit. The peak is 96B/clock, but apparently that can't happen back-to-back indefinitely.
One downside to stopping store-address uops from running on p23 is that it would take longer for store addresses to be known, maybe delaying loads more.
I can't understand when store-forwarding on the data (aka: STD / Port 4) would ever be done.
A store/reload can have the load take the data from the store buffer, instead of waiting for it to commit to L1D and reading it from there.
How does store to load forwarding happens in case of unaligned memory access?
Store-to-Load Forwarding and Memory Disambiguation in x86 Processors
Store/reload can happen when a function spills some registers before calling a function, of as part of passing args on the stack (especially with crappy stack-args calling conventions that pass all args on the stack). Or passing something by reference to a non-inline function. Or in a histogram, if the same bin is hit repeatedly, you're basically doing a memory-destination increment in a loop.
Its been a few days without a response, so here's my best guess at "answering my own question".
The raw x86 instruction set isn't executed directly by modern processors. Instead, the x86 instruction set is "compiled" down into Micro-ops (uOps) before being executed by the Intel core. This shouldn't be too surprising, because some x86 instructions can be complex. An example taken from the optimization guide is as follows:
Similarly, the following store instruction has three register sources and is broken into "generate store
address" and "generate store data" sub-components.
MOV [ESP+ECX*4+12345678], AL
This is currently found on page 50 of the optimization manual (2.3.2.4 Micro-op Queue and the Loop Stream Detector (LSD)).
In this case, the address of the store operation is complex, so it is its own uOp. So at very least, this singular x86 instruction gets converted into two uOps internally. The names of these two uOps are "Store Address" and "Store Data". The manual doesn't describe the internal uOps at all, so it may take even more than two uOps to accomplish.
Since there's only one "store data" port on Skylake systems, that means that Skylake can only modify at most one memory location per cycle. The three "Store Address" ports means that Skylake can calculate the effective address of many instructions simultaneously (possibly because some very complicated addresses may take more than one uOp to execute??).

What is the more reliable way, using the Win32 API, to determine if a processor is an Intel Skylake Gen?

What is the most reliable way, using the Win32 API, to determine if a processor is an Intel Skylake Gen? This seems like an easy question, as one can check the friendly name of the CPU in the registry and get some data, but I have found that to be less than authoritative and feel I am missing some other store of data to query.
Note: I specified the Win32 API to both be clear this is Windows, and also to deter answers that would involve writing a device driver (interfacing with them via deviceioctrl/IRP is fine).
Thanks!
Probably the most reliable / direct way is to use the CPUID instruction with the appropriate input register values, and decode the vendor/family/model ID numbers.
According to http://www.sandpile.org/x86/cpuid.htm,
SKL has Family = 0x6 (like every descendant of i686 PPro (P6 core)).
SKL Y/U: model = 0x4E (low power, dual-core even for i7)
SKL S/H: model = 0x5E (desktop/high-power laptop, quad-core except i3)
SKX model = 0x55 (Skylake-E Xeons, not release yet AFAIK)
KBL Y/U: model = 0x8E (Kaby Lake low power, dual-core)
KBL S/H: model = 0x9E (Kaby Lake desktop/high-power laptop, quad-core except i3)
Dual-core desktop i3 CPUs are probably the same die as quad-core i5, but with 2 of the cores disabled. (Often because of a manufacturing defect that would prevent it being sold as a quad-core part.) Interesting to see that the model # reflects this difference between dual-core silicon vs. a quad-core die fused-off to dual-core.
If there's something you want to enable based on something Skylake has, it might be better to detect that directly (with some other CPUID query). e.g. check the feature-bit for an instruction-set extension directly. That way you won't run into trouble in a VM where CPUID shows a SKL CPU, but the VM doesn't pass through all instruction-set extensions. (e.g. some don't pass through AVX to the guest OS).
But this might be useful if you're selecting between versions of a function tuned for Haswell vs. Skylake. e.g. psrlvd ymm, ymm, ymm is 1 uop / 1 cycle on Skylake, but 3 uops and 3 cycles on Haswell. So on Haswell, repeated shifts by the same amount (when it isn't a compile-time-constant) would be faster if you use psrld ymm, ymm, xmm (with the count in the low element of the xmm reg), but on Skylake it's faster to pre-broadcast the shift count and use a variable-shift.
There are other improvements to front-end throughput, micro-fusion of indexed addressing modes, and instructions running on more ports that could make it useful to have differently micro-optimized versions of things for Skylake vs. Haswell.
(answering my own question)
While no available way using the Windows API became apparent, I found and excellent summation at https://en.wikipedia.org/wiki/CPUID.
Using the CPUID instruction, one can derive the model based on the highest supported feature count, returned in the EAX register; coupled with vendor (returned elsewhere). I now have a nice abstraction layer for all this.
Here is a list of processors and the highest function supported: https://en.wikipedia.org/wiki/CPUID
For Skylake CPUs, this is 0x16 (32).
History shows this to be unique for CPU models (see link).

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