[0]: https://www.youtube.com/watch?v=nhXevKMm3JI&list=PLzH6n4zXuc...
[1]: https://www.youtube.com/watch?v=nczJ58WvtYo&list=PLzH6n4zXuc...
Whatever Web App Scaling issues we had in 2014 could now fit into a single server, assuming we somehow manage to cool the thing. Even at 1 RPS per vCPU that is 1000 RPS, excluding cache hit. Even on HN front-page dont hit the server at 1000 Page View per second.
I wonder what about its HPC performance. I think cooling this won’t be big problem, but might be wet one, requiring DLC after a certain point.
It's hard to be network I/O bound when serving web pages. Netflix struggles to be network I/O bound when serving video, which is so much bigger and uses so much less processing.
Epyc started off with 32 cores on PCIe 3, and quickly moved to 64 cores on PCIe 4. When we hit 256 cores it's probably going to have PCIe 6, which means it's still the same I/O per core.
But those numbers are crazy overkill for web serving anyway. If you wanted to allocate about a gigabit per core, with 512 cores across two CPUs, using PCIe 5 to be conservative, you'd need at total of... 16 lanes, for a single 400gb/s card you can buy today.
(This is assuming you mean the I/O from the server to the network. If you're talking about I/O outside the server, then upgrade your switches. Using denser servers doesn't increase your network load, it lets you take the same load and send it to fewer racks. You're already handling the total data somewhere.)
Terabit Ethernet also is easy. Just 10 100gbit fibers. Again, not much either in port count, or in physical space needs (port count is ample, fibers are thin).
What I meant is, in a conventional data center, you'll probably hit your allocated bandwidth limits before you saturate a processor like this while serving web pages, unless you're sitting on a big exchange point or the backbone router is not in the next system hall. A single socket Epyc system has 128 PCIe lanes and 12 channel memory. A complete overkill for such a job unless you serve millions, and only have a basement to put your servers with some very fat network pipes.
If your actually-kept-busy servers get 20x faster and your allocated bandwidth doesn't, there's a point where your racks are almost empty and you have some issues to address with the datacenter owner.
Add to that the 12 channels of DDR per socket and the quite generous cache, and once you've swallowed the need to buy 24 sticks for 2 sockets, these things are beautiful beasts, at what Intel has taught us, a very reasonable price (ask you OEM for prices, public prices on CPUs are nuts).
I found it entertaining having a debate with someone here on HN who just couldn't grok the concept that it's possible to serve something the size of Wikipedia from a single server. That's been easy for a while now, it just isn't done for practical reasons such as availability or cost-efficiency.
One of the main benefits of a CDN is that it brings the data closer to the users, reducing network latency. Obviously a single server can’t be close to every user globally!
In practice one would always use a CDN for a site like WikiPedia but the point is that it isn’t necessary to handle the traffic.
A single two-socket EPYC server can put out something like 400 Gbps of traffic, which is far more than all but the biggest sites.
Intuitively having more tasks working on the same problem at half speed should have a memory usage cost, are apps commonly using more memory for no speed gain when using SMT?
In a lot of published benchmarks it seems most apps don't noticeably benefit in executions peed.
Other things making up the potential for being more than a zero sum game (half the speed) include making better use of the ALU and branch units that would otherwise be waiting for dependencies. On the other side of the scale is how different working sets of the threads can thrash each others cache working sets.
The power9 4-way SMT seems to be a fair bit more effective than what I've seen on x86.
For example Z-buffers[1]. It's used by 3d video games. When it's first published on paper, it's not even the main topic of the paper, just some side notes because it requires expensive amount of memory to run.
Turn out megabytes is quite cheap few decades latter, and every realtime 3d renderer ended up using it.
The first mainstream use was in 2003. It is now used in WiFi, Ethernet and 5G.
[1] https://en.wikipedia.org/wiki/Low-density_parity-check_code
[2] https://scholar.google.com/scholar?q=%22low+density+parity+c...
I remember one bit where a species had launched some tricky fleet-destroying weapon to surprise their enemies with esoteric physics, only to have it reversed against them, possibly because the Librarian that once helped their research-agent wasn't entirely unbiased.
I'd have thought asking for a spoiler alert would be pretty acceptable.
Is a spoiler alert.
Also:
> Please don't comment about the voting on comments. It never does any good, and it makes boring reading.
"When Soviets Won the Cold War: Wading Through Pyotr Ufimstev's Work on Stealth" (26.03.2024)
https://news.ycombinator.com/item?id=39830671
> In the early 1970s, Lockheed Martin engineer Denys Overholser discovered the key to stealth technology hidden in a stack of translated Soviet technical papers. Disregarded by the Soviet academic elite, and unheard of in the United States, Pyotr Ufimstev had worked out calculations that would help win ...
Not sure of the details of this story, but in general having there enough people to grant them time just to search for something interesting seems not unrealistic.
That worked eventually and worked quite well, but took way more compute and training data that anyone back in the olden days would have thought feasible.
The two main problems with sigmoid activation compared to ReLU are: (a) harder to compute (both the value itself and the gradient), and (b) vanishing gradients, especially in deeper networks.
At least one of them is very, very specific and is the one that Wikipedia uses in https://en.wikipedia.org/wiki/Real-time_computing
> Real-time computing (RTC) is the computer science term for hardware and software systems subject to a "real-time constraint", for example from event to system response.[1] Real-time programs must guarantee response within specified time constraints, often referred to as "deadlines".[2]
Strictly speaking, this definition doesn't say anything about how tight those deadlines are, as long as you can guarantee some deadlines.
There's also 'soft' real time where you try to hit your deadlines often-enough, but there's no guarantees and a missed deadline is not the end of the world. Games are good example of that, including the example of chasing the electron beam.
ABS brakes are an example of a 'hard' real time system: the deadlines aren't nearly as tight as for video game frames, but you really, really can't afford to miss them.
A human can only read so much, so has to discriminate. But our machines are omnivorous readers.
I'd rather say that we were capable of such a design for several decades, but only now the set of trade-offs currently in-place made this attractive. Single core performance was stifled in the last 2 decades by prioritizing horizontal scaling (more cores), thus the complexity / die area of each individual core became a concern. I imagine if this trend did not take place for some reason, and the CPU designers primarily pursued single core performance, we'd see implementation much sooner.
Regarding the Z-buffer, I kind of get that this would appear as a side note, it's a simple concept. Perhaps even better example is ray tracing - the concept is even quite obvious to people without 3D graphics background, but it was just impractical (for real-time rendering) in terms of performance until recently. What I find interesting is that we haven't found a simpler approach to approximate true to life rendering and need to fallback on this old, sort of naive (and expensive) solution.
Could you elaborate on that?
Affine logic only says what you're able to do with a value, it doesn't say anything about what happens when that value goes out of scope.
Early 3D, especially gaming related, implementations didnt have any expensive per pixel calculations. Cost of looking up and updating depth in Z-buffer was higher than just rendering and storing pixels. Clever programming to avoid overdraw (Doom sectors, Duke3D portals, Quake sorted polygon spans) was still cheaper than Z-Buffer read-compare-update.
Even first real 3D accelerators (3Dfx) treated Z-buffer as an afterthought used at the back of fixed pipeline - every pixel of every triangle was being brute force rendered, textured, lighted and blended just to be discarded by Z-buffer at the very end. Its very likely N64 acted in same manner and enabling Z-buffer didnt cut the cost of texturing and shading.
Z-buffer started to shine with introduction of Pixel Shaders where per pixel computations became expensive enough (~2000 GF/Radeon).
Wiki tells me: <<Earliest eligible virtual deadline first (EEVDF) is a dynamic priority proportional share scheduling algorithm for soft real-time systems.>>
Ref: https://en.wikipedia.org/wiki/Earliest_eligible_virtual_dead...
The (string) garbage collector was amazingly frugal and correspondingly slow. Because the garbage collector typically ran only when memory was critically low it used almost no memory, just 4 bytes I think. (it was also possible to invoke it any time with the FRE(0) function call IIRC)
The routine would sweep all of the symbol table and expression stack looking for string pointers, and would remember the lowest (highest? I forget which) string base address which hadn't already been compacted. After each pass it would move that one string and fix the symbol table pointer (or expression stack str pointer) then do another pass. As a result, is was quadratic with the number of live strings -- so if you had a large number of small strings, it was possible for your program to lock solidly for 30 seconds or more.
As for how to stop that, short of boiling the ocean[0], you don't. Speculative execution is so valuable for performance that a computer without it is completely unusable. If you really want a processor without it, buy an old first-gen Pentium.
Actual practical mitigations for speculative execution vulnerabilities are varied, but at a minimum you have to ensure process separation between a victim process holding secrets and any potential attackers that may have the opportunity to influence victim process execution. Intel was caught with their hands in their pants speculating across rings, which is why you could read kernel or hypervisor memory from userspace, but on not-poorly-designed CPUs the main victim you have to worry about is HTML iframes. Different origins aren't allowed to make HTTP requests to one another[1], but they can transclude[2] one another without permission. That traditionally loaded information from the origin into the attacker's process, which could be exfiltrated with timing attacks.
The web's solution to this was actually not to process-separate iframes, at least not initially, but to take away shared-memory multithreading entirely. If you deny the attacker a timing reference then it doesn't matter what they can make the victim speculatively execute. But to do this you have to take away multithreading because otherwise a thread can just repeatedly write known data in a loop to create a clock.
[0] https://hackaday.com/2013/08/02/the-mill-cpu-architecture/
[1] At least not without the target origin allowing it via CORS
[2] e.g. hotlink images or embed iframes
Jim Keller's view aligns with this and goes further. My interpretation of his thinking is that predictors and speculation are the only meaningful features of CPUs today. ISA doesn't matter anymore because the power of modern compilers makes high performance software highly portable and all CPUs end up bottlenecked on the quality and capacity of the predictors, regardless of the ISA. For example, the burden of x86 complexity no longer matters because it amounts to a "tax" small enough to be lost in the noise.
That's from a designer making high performance RISC-V CPUs.
ISA doesn’t matter any more because all the CISCiest CISCs and the RISCiest RISCs have been discarded (except for RISC V…) so modern CPUs don’t have to cope with multiple memory addresses per instruction or indirect addressing.
Keller specifically addressed this. His view is that yes, the x86 instruction width problem is real, but it's not an important performance bottleneck because decoders are now sophisticated enough that other bottlenecks (predictors) dominate the net performance. Yes, this means more power usage and die area, but only a part of the market is sensitive to this: where other considerations dominate the cost premium of x86 can be ignored.
He also believes that "RISC-V is the future of computing," (not surprising from the CEO of a RISC-V vendor,) so it isn't as if the legacy ISAs are somehow just fine. But ISA complexity isn't the key determinant in that future. The keys are the open ISA, commoditization of designs and high software portability.
This makes sense to me. x86, despite it's inherent issues, has fought off alternatives before. But now, as per Keller, there is a Cambrian explosion of RISC-V designs appearing, and what emerges from that is going to prevail against any legacy ISA, not just x86. Ulitimately, therefore, the x86 "tax" doesn't actually matter.
Not in general they don't. Apple's does, and Qualcomm's newest Snapdragon X Elite also does. But most big ARM cores don't have larger decode widths than x86 cores. The Cortex-A78 is a 4-wide decode, same as the majority of x86 CPUs on the market. ARM's latest & greatest Cortex X2 is only a 5-wide decode, it only just finally surpassed the original Zen design (4-wide).
Also Zen 5 bumps to an 8-wide decode, the same as what Apple & Qualcomm's best ARM chips can do.
RISC was not just about total instructions, but the complexity of those instructions. It's fundamental conceit is that every instruction should ideally take just one cycle to execute. Intel's iAPX432 is one of the most CISCy designs out there and a great case that ISA does matter. It had instructions for stuff like data structures, OOP, and garbage collection. These things could take LOADS of cycles to execute.
In contrast, pretty much everything on ARM64 integer spec is going to execute in just a cycle or two.
> In contrast, pretty much everything on ARM64 integer spec is going to execute in just a cycle or two.
integer spec is the keyword here. ARM CPUs these days implement much more than integer spec. "If I ignore everything else, it's RISC" is not a good argument IMHO.
Isn't Thumb-2 for 32-bit ARM only? AFAIK, having 32-bit ARM is optional, you can have 64-bit only ARM nowadays.
(And 64-bit ARM no longer has what is IMO the least RISC instructions from 32-bit ARM: the "load multiple" and "store multiple" instructions, which had a built-in loop doing memory accesses to an arbitrary set of registers, were replaced by "load pair" and "store pair", which do a single memory access and work with a fixed number of registers. If you look at https://www.righto.com/2016/01/more-arm1-processor-reverse-e... you can see that the circuitry dedicated for these instructions took a lot of space in the original 32-bit ARM core.)
AES in ARM (and x86 as this was after their attempt to be more RISC-like) was designed to be RISC. A CISC approach would have just ONE instruction that would take the data pointer and number of rounds then do everything at one time. In contrast, x86 and ARM use a couple simple setup instructions, then an AES round instruction (1-2 cycles) that gets called repeatedly then a couple more finalizing instructions.
If you look at the code on any machine, something like 95+% of it is integer code. Integers are fundamental and everything else is a performance optimization.
The float/vector pipeline is a different thing, but it still takes a RISC appoach. 1-5 cycles for most things, a few are 6-7, and a couple like divide and some types of sqrt can take up to a dozen or so cycles (there's a reason they are avoided). This all happens in its own separate pipeline with its own scheduler. All the ideas of being superscalar and avoiding bubbles apply here too. Even the worst case is a far cry from CISC chips where instructions could take dozens or even hundreds of cycles.
Most CISC designs died. A large part of x86's survival is because it wasn't exceptionally CISC.
Make a Rosetta analog and translate to an instruction set that is amenable to efficient prediction, wide dispatch, etc., replacing all the iAPX hardware object oriented nonsense with conventional logic. If necessary, extend the CPU to accommodate whatever memory ordering behavior is necessary for efficient execution, ah la Apple Silicon ARM with x86 total store ordering.
Pentiums have branch prediction and speculative execution. You need to go back to i486 if you don't want speculative execution. Most of the socket 5/7 processors from other makers also had branch predictors and speculative execution, but not the Centaur Winchip. The Cyrix 5x86 for socket 3 (486) had speculative execution, but it was disabled by default and is reported to be buggy (but helps performance on published benchmarks).
Even 486 (and possibly 386) had branch prediction (although a trivial one).
P6 was a huge deal because it added out of order execution.
Edit: I guess it is a matter of semantics: in the classical 5 stage in order RISC, instructions after the speculated branch are fetched, decoded, etc, but they won't reach the execution stage before the speculation is resolved, so only the branch is technically "executed" speculatively at the fetch stage. So there is less state to unwind, compared to a true OoO machine that can run ahead.
P5 has a more 'real' BP but also had the U/V Pipelining.
But yes as far as OoO goes, I think for x86 it was Nx586 first, then PPro (P6), then Cyrix 6x86 [1] and AMD K6 (courtesy of Nextgen tech) the next year.
[0] - https://people.computing.clemson.edu/~mark/330/colwell/case_...
[1] - Worth noting the Cyrix Coma bug, which was a way to express a flaw in the pipeline. https://en.wikipedia.org/wiki/Cyrix_coma_bug
I guess calling this speculative execution is a stretch.
What it didn't have is out of order execution, which greatly increases the speculation window.
Amd, for example, has observability issues in all zen1/2/3 processors that leaks enough data to break KASLR that remain unpatched in all chips except for Milan (specifically epyc only, not ryzen). They didn’t expect cache ways to be visible in that fashion, and it’s observable that the model is incorrectly implemented.
the idea cannot fail, only be failed, because if it’s observable then obviously you just did it wrong.
So, to your original question, we're always going to have prediction, and we're going to have to solve any vulnerabilities that arise downstream. Which, thankfully, is always an available option.
Multiple-block ahead branch predictors
Abstract:
A basic rule in computer architecture is that a processor cannot execute an application faster than it fetches its instructions. This paper presents a novel cost-effective mechanism called the two-block ahead branch predictor. Information from the current instruction block is not used for predicting the address of the next instruction block, but rather for predicting the block following the next instruction block. This approach overcomes the instruction fetch bottle-neck exhibited by wide-dispatch "brainiac" processors by enabling them to efficiently predict addresses of two instruction blocks in a single cycle. Furthermore, pipelining the branch prediction process can also be done by means of our predictor for "speed demon" processors to achieve higher clock rate or to improve the prediction accuracy by means of bigger prediction structures. Moreover, and unlike the previously-proposed multiple predictor schemes, multiple-block ahead branch predictors can use any of the branch prediction schemes to perform the very accurate predictions required to achieve high-performance on superscalar processors."
[0] https://dl.acm.org/doi/10.1145/237090.237169
EDIT: oops. Looks like eyegor posted the link earlier. Oh well, enjoy the abstract.
Given that, I still don’t understand how predicting the next two branches is different from predicting the next branch and then the next after that, i.e. two times the same thing.
A branch predictor result is just a tuple of ("branch instruction address", "branch target address") that hints the processor that when the CPU will encounter a given branch instructions in the future (at "branch instruction address") it will likely branch to the branch target and so it would make sense to start fetching that address and filling the instruction pipeline with whatever steps are safe to perform before the jump will be actually performed.
Now, commonly this branch happens to be at the end of the current basic block and I assume some branch predictors may also leverage this fact in order to encode only offsets from the current instruction pointer.
But there is no reason why the branch location might be after some other branches may be taken. As long as the cpu eventually gets to that branch location the prediction will be useful. If the IP never reaches that location it's like the branch was never actually taken.
I'm not involved in CPU design, I just read a lot, but...
I think you need to do something special to have a second prediction, because you have to track three windows of out of order execution:
Window 0: code you're definitely running but is still being completed.
Window 1: code from the branch you think will be taken
Window 2: code from the 2-ahead branch you think will be taken.
If you figure out that the window 1 branch isn't taken, you have to drop the whole pipeline (pipeline bubble). But if you figure out that window 1 is taken, then window 1 becomes window 0 and window 2 bcomes window 1.
With a 1 ahead predictor, the pipeline stalls if you get to a conditional branch while speculating in window 1, because the processor can't manage three instruction windows.
IMHO, it sounds like if the core is doing SMT and both threads are active, each thread only gets 1-ahead prediction because the two windows are statically divided between the cpu threads. This may mean a) a significant boost for some loads when SMT is not in use and b) SMT can branch predict in both threads in the same cycle, I don't think that was possible on AMD before (no idea for other vendors)
So the question remain, what's the innovation here? I'm sure there is something, but it is not simply speculating two ahead.
I need tor was further, bit this might be an optimization in the fetched tage to avoid a bubble when fetching consecutive taken branches.
if (a) { ... }
if (b) { return x; } else { return y; }
The two branches can be wholly independent, but predicting the second is still a two-ahed prediction.I'd think if you are at PC N and there are branches at N+1 and N+2, predicting just branch N+2 is fine because you predicted the N+1 branch previously, at PC N-1.
> Zen 5 can look farther forward in the instruction stream beyond the 2nd taken branch and as a result Zen 5 can have 3 prediction windows where all 3 windows are useful in producing instructions for decoding.
The original paper is open access but I haven't read far into it: https://dl.acm.org/doi/10.1145/237090.237169
The frontend is already predicting dozens of branches ahead of what the backend can actually confirm. Looking ahead by one extra branch ahead doesn't really hurt.
Also, modern TAGE branch predictors are scary accurate, well above 99% on most code (including unpredictable indirect jumps). Besides, the majority of branch prediction targets are already in the L1 cache, it only predicts them because it saw them recently.
The branch predictor in Apple's M1 actually takes advantage of the latter fact. It doesn't predict what address to fetch next, it predicts which cacheline in L1 holds the target. So you only actually get branch predictions for targets in L1.
I suspect Apple are also using it as a way predictor. If the BTB points directly to the correct cacheline and each cacheline points to the next way then the only time you need to do a search is on a branch misspredit.
Each side of the branch leads to the start of a new block of instructions. The last instruction of such a block is usually another branch.
In other words, a branch predictor guess the address of the next block. A 2-ahead branch predictor does the same thing, but for the two subsequent blocks.
As stated in the paper: "information from the current instruction block is used for predicting the address of the block following the next instruction block".
Unlike a regular branch predictor, it can do that without having to wait for instructions in the next block to be decoded. That way, you can feed multiple instruction decoders at once.
This is particularly useful in modern CPUs where the instruction decoder has become a bottleneck. With only 1 decoder and 1 instruction decoded per cycle (at best) it cannot cope with a wide frontend that can execute many instructions (eg: 4-6) per cycle.
Cold, warm, warmer, omit hot as it is the default? Sometimes you would set all branches to be cold except one
why when we have a conditional branch we cannot just fetch and prepare instructions for both possible branches and then discard the incorrect one?
is this that much harder or there are other reasons that makes this not worth it
A modern TAGE branch predictor is correct well over 99% of the time. So those extra instructions for the other side of the branch are almost always discarded.
Worse, the frontend is fetching dozens of branches ahead of where the backend can actually confirm which direction to take. What are you going to do at the next branch, start decoding four possible branches? then 8, 16, 32 possible branches? Remember, most of the time you are going to throw it away.
If you actually have the hardware to fetch from multiple instruction streams in parallel (which Intel's Gracemont/Goldmont/Skymont and now AMDs Zen 5 do), the better strategy is to assume your branch predictor is actually correct 100% of the time. Follow one side of the branch, then the one after it.
Intel's Skymont actually decodes the next 3 branch targets in parallel because it has three decoders, each 3-wide. Intel actually introduce fake branches to break up large blocks of code, so that all three decoders are always active decoding different part of the upcoming instruction stream. The three uop streams are later merged, allowing Skymont to maintain an effect decode bandwidth of 9 instructions per cycle.
If you executed both sides of the branch, you are only slightly reducing the branch misspredit delay in the rare case the branch prediction was wrong. Instead, by executing one side the next two or three predictions, Intel and AMD can make multiple decoders do work in parallel. Intel are doing 9-wide with three simpler 3-wide decoders, and AMD can do 8-wide with two simpler 4-wide decoders.
Intel have actually implemented a 6-wide decoder for Golden Cove, but they must really be pushing the limits of propagation delays. So it's attractive to just use two or three smaller decoders in parallel.
> If branches can be used in this way, unconditional jumps (e.g. gotos) and function calls can probably be used for similar purposes.
It's a common misconception that the branch predictor only predicts conditional branches. They need to predict anything that causes control flow to diverge. So unconditional branches, calls, returns, and maybe even syscalls, all count as "branches" and get handled by the branch predictor.
(On most RISC instruction sets, these instruction are often labeled branch. Call is just "Branch And Link" which saves the return address in a register. To return, you just use the "Branch to Register" instruction)
This is necessary because the frontend is pipelined. It takes a minimum of four cycles to fetch the instruction data from instruction cache and decode it before the frontend can even know there is a call, return or unconditional branch instruction. If we are decoding four instruction per cycle, we are already 16 instructions past the branch before we even know it's there, and it's common to have a branch every 3-4 instructions.
Basically, the frontend is blind and can't see any branches.
Predicting the direction of conditional branches is almost a secondary task for modern branch predictors. It's much more important to predict where the branches are and their destination, so that instruction fetch stage can request the correct data from the instruction cache and keep the pipeline fed.
I think a lot of people don't have an intuition about how accurate branch prediction can be, but if you look at your own code, you'll quickly realize "well, yeah, control flow is almost always going to go this way and we just have this branch so we can handle the exceptional case" -- compilers can often deduce this pretty well themselves now, and cpus/jits/runtimes can develop some pretty impressive heuristics as well, and when all those fail you can often add explicit hints in your code that tell your compiler/etc what you expect if they can't guess.
How rare, though?
QuickSort has fundamentally unpredictable branches, and it’s a pretty widely used algorithm. Binary search, B-trees also come to mind.
It's also definitely going to depend on the cost of the hash function and comparison function - for something like strings, where those can be quite expensive, binary search probably has a better chance of applicability than for guid's say.
As far as I can tell, branch predictors have always been too good for it to be worth it. Moderns CPUs have instruction reorder buffers that are hundreds of instructions deep, so even if only 8 of those instructions are conditional jumps, there's 256 different paths your program could take. If your branch predictor predicts all 8 correctly >50% of the time (It does), doing 256x the work to cover your ass is not worth it.
It requires more silicon to hold more microarchitectural state and more execution units to fully exploit the technique, but superscalar CPUs already have those since they are essential to exploit instruction level parallelism in non-branchy code. The rest is "just" a lot of headaches to handle complicated stuff such as aliasing, interrupts, ... But hardware engineers are such wizards they can do these things too.
Turns out however that speculative execution opens up a possibility of abusing a cache timing side channel to extract information from data touched by branches of code that has been only speculatively executed but whose architectural side effects were not committed (i.e. not "really" executed).
Which includes code that had been explicitly not executed because of a conditional check (e.g. permissions, ...)
A familiar instance of such an attack is Spectre [1]
1: https://en.m.wikipedia.org/wiki/Spectre_(security_vulnerabil...
So basically it’s just nowhere near worth it. Much better to use those chip resources for another thread or core.
You could potentially do it only for predicted "unpredictable" branches. Now the tradeoff is wasted power and execution units for dead work and so far the tradeoff was just not worth it.
Some form of this has been experimented with. In the late '90 SPRC experimented with scouting threads and as mentioned else thread the Efficient Intel cores can fetch (but not execute) across branches.
- Double the execution units; very expensive for wide vector units
- Massive waste of energy as half the resources will always be wasted no matter what
- Bad scaling, i.e. four branches ahead would require 16x the resources
Doubling the execution units also isn't strictly needed - you can use the existing out-of-order core to send two sets of instructions through the same functional units. There will be more contention for the resources, possibly causing stalls, but you don't need to fully double everything.
Things similar to this idea are already done in processors - simultaneous multithreading, early branch resolution, conditional instructions, are all ideas that have similar implementation difficulties. So the reason this specific idea is not done is more in line with your last two points rather than the first two.
I say the SMT core would be reduced by one since, rather than being used as an SMT core, it would be used as the second branch prediction thing.
We actually do that. It's called a GPU. And it sucks for general code.
Anyway, I think the intuition of this approach is to aggressively fetch/decode instructions that might not already in L1 instruction cache / micro-op cache. This is important for x86 (and probably RISC-V) because both have varied instruction length, and just by looking at an instruction cache block, the core wouldn't know how to decode the instruction in the cache block. Both ISAs (x86, RISC-V) require knowing the PC of at least one instruction to start decoding an instruction cache block. So, knowing where the application can jump to 2 blocks ahead helps the core fetching/decoding further ahead compared to the current approach.
This approach is comparable to instruction prefetching, though, instruction prefetching does not give the core information about the starting point.
(High performance ARM cores probably won't suffer from the "finding the starting point" problem because every instruction has the length of 32-bit, so the decoding procedure can be done in parallel without knowing a starting point).
This approach likely benefits front-end heavy applications (applications with hot code blocks scatter everywhere in the binary, e.g., cloud workloads). I wonder if there's any performance benefit/hit for other types of applications.
In general, the older research papers suppose that the reader knows much less about such subjects, because they were still much more niche knowledge at that time.
A 2-ahead branch predictor is a branch predictor that predicts not which block to run next after the current one, but rather, which block should be run after that one.
I moved to an M2 Max from a chunky Zen setup and it's a revelation how much the memory bandwidth improvement accelerates intensive data work. Also for heavy-ish multitasking the Zen setup's narrow memory pipe would often choke.
The reason people have been looking at Apple Silicon for LLMs in particular is that even though they are more suited to GPUs, they also require a lot of VRAM and NVIDIA charges an extortionate amount of money for GPUs with a lot of VRAM.
What AMD should really do if they want to steal NVIDIA's thunder is to sell consumer GPUs with 64-128GB of VRAM.
For gaming, it's an overkill (esp. given the price), it would be useful only for LLM enthusiasts which isn't that big of a market.
Nobody said it was for gaming. Though of course consumers could use it for both.
And from what I hear they're selling every one they're producing, even to the level where there's a ~6 month waiting list. So even if they reduced the price, the only difference would be that the list would get longer and AMD got less money. No more devices would actually make into people's hands, being production limited.
This might even leave gamers with more GPUs, because right now there are people buying e.g. four 24GB consumer GPUs to run a large model, and they could instead buy one 96GB GPU and leave three more for gamers.
They're intentionally differentiated in the market and marked up due to the relatively higher R&D costs from targeting a much smaller market niche, with it's own demands on development. I doubt you'll just be running games on them, after all.
If that is your niche, AMD is effectively saying they don't want your custom at that price. No point selling products that lose money, after all. AMD have done it before - arguably are doing it right now as their graphics BU lost money last year if you exclude APUs and consoles - and it went badly each time (despite what some people say about "Market Share!" on some internet forums).
Not doing that is making a mistake.
There are actually four memory channels in AM5, because DDR5 doubles the number of channels.
This sounds like a big boost for hyper threading performance. My Zen1 gets about 25 percent faster due to HT. Has anyone tested the newer ones in this regard?
The ideal speedup from SMT is 0% because you’d be getting full output for a single thread. Like if you got a 50% speedup from SMT, in an ideal world that means a single thread could run 50% faster than it is, but it’s being stalled by pipeline bubbles.
That's rare though. All it takes is a couple stalls waiting on memory where a second thread is able to make progress to make that "ideal speedup" certainly be nonzero.
I'll give another example from my own experience. I write a lot of code in the computer graphics domain. Some of the more numeric-oriented routines are able to saturate the execution resources, and get approximately 0% speedup from SMT.
Importantly though, there are other routines that make heavy use of lookup tables. Even though the tables reside completely within L1 cache, there are some really long dependency chains where the 3/4 cycle wait for L1 chains and causes some really low utilization of ALUs. Or at least, that's my theory. :) Regardless in that code running SMT provides about a 30% speedup "for free" which is quite impressive.
I was uncertain of if SMT had a future for a while, but I think for x86 in general it provides some pretty significant gains, for a design complexity that has already been 'paid' for.
However you are right that Zen 5, like also the Intel Lion Cove core, has a jump in the number of available execution resources and it is likely that out-of-order execution will not be enough to keep them busy.
This may lead to a higher SMT gain on Zen 5, perhaps on average around 30% (from typically under 20% with Zen 3 or Zen 4), like in the Intel presentation where they compared a Lion Cove without SMT with a Lion Cove with SMT. In the context of a hybrid CPU, where the MT-performance can be better provided by efficient cores than by SMT, Intel has chosen to omit SMT, for better PPA (performance per power and area), but in the context of their future server CPU with big cores, they will use cores with SMT (and with wider SIMD execution units, to increase the energy efficiency).
Because SMT getting faster is a nearly free side-effect. We didn't add extra units to speed up SMT at the cost of single-thread speed. We added extra units to speed up the single thread, and they just happened to speed up SMT even more (at least for the purpose of this theoretical). That's better than speeding up SMT the same percent, or not speeding up SMT at all.
Imagine if I took a CPU and just made SMT slower, no other changes. That would be a bad thing even though it gets the speedup closer to 0%, right? And then if I undo that it's a good thing, right?
https://old.reddit.com/r/hardware/comments/1ee7o1d/the_amd_r...
this isn't adding more units to speed up single-thread and SMT being a nice "incidental" gain, this is actively targeting wide architectures that have lots of pipeline bubbles for SMT to fill.
and that's fine, but it's also a very different dynamic than, eg, apple silicon, where the focus is running super deep speculation and reordering on a single thread.
The returns are diminishing, but a single digit bump is still a pretty good when your goal is faster single threads.
Adding nothing to save space is obviously not the answer, because that leads to having more slower cores.
Also the topic of the post, the 2-ahead branch predictor, exists specifically to get more ALUs running in parallel!
> apple silicon, where the focus is running super deep speculation
And to make that speculation profitable, the M1 cores have 6 ALUs among other wideness.
An example of a multithreaded benchmark that is not SMT friendly is the GeekBench 6 multithreaded test, where Zen 3 with SMT disabled (12 threads on a 5900X) is slightly faster than with SMT enabled (24 threads on a 5900X).
I have CPUs with 48 threads and for big projects the compilation time decreases monotonically from 1 thread to 48 threads (and almost proportionally with the number of threads until 24 threads, then with a constant smaller slope until 48). The published benchmarks show that for big software projects the compilation times decrease monotonically until 512 threads on a 2-socket MB with 128-core CPUs.
So the compilation of a big software project, like Chromium, Firefox, LLVM, gcc, the Linux kernel, Libreoffice, etc. (all of which have many thousands of files that must be compiled) is one of the tasks that can use efficiently any number of threads that is currently available.
Moreover, there are now linkers that work partially concurrently. Tasks like the relocation of the object files and of the external symbol references can be done completely concurrently for all source files (after the start addresses are known for all object files and the corresponding object files are known for each symbol).
On the contrary, he points that one of their most important innovations is not that innovative, because it was analyzed in detail almost 30 years ago.
Before AMD, Intel had started to use such multiple decoders in their Atom cores, now rebranded as E-cores (efficient cores). The multiple decoders have been first used in Tremont (2020), then in Gracemont (2021) and Crestmont (2023), and now in Skymont (2024).
It is hard to predict which of the decoders of Skymont (triple 3-instruction decoder) or of Zen 5 (double 4-instruction decoder) is better. AMD has made the choice of the double decoder because their core uses SMT, and a double decoder is easy to be partitioned into two decoders when both simultaneous threads are active.