We're hiring!
*

Reverse-engineering the Mali G78

Alyssa Rosenzweig avatar

Alyssa Rosenzweig
July 20, 2021

Share this post:

Reading time:

After a month of reverse-engineering, we’re excited to release documentation on the Valhall instruction set, available as a PDF. The findings are summarized in an XML architecture description for machine consumption. In tandem with the documentation, we’ve developed a Valhall assembler and disassembler as a reverse-engineering aid.

Valhall is the fourth Arm® Mali™ architecture and the fifth Mali instruction set. It is implemented in the Arm® Mali™-G78, the most recently released Mali hardware, and Valhall will continue to be implemented in Mali products yet to come.

Diagram of Mali architectures: Utgard GP and PP; Midgard; Bifrost; Valhall

Each architecture represents a paradigm shift from the last. Midgard generalizes the Utgard pixel processor to support compute shaders by unifying the shader stages, adding general purpose memory access, and supporting integers of various bit sizes. Bifrost scalarizes Midgard, transitioning away from the fixed 4-channel vector (vec4) architecture of Utgard and Midgard to instead rely on warp-based execution for parallelism, better using the hardware on modern workloads. Valhall linearizes Bifrost, removing the Very Long Instruction Word mechanisms of its predecessors. Valhall replaces the compiler’s static scheduling with hardware dynamic scheduling, trading additional control hardware for higher average performance. That means padding with “no operation” instructions is no longer required, which may decrease code size, promising better instruction cache use.

All information in this post and the linked PDF and XML is published in good faith and for general information purpose only. We do not make any warranties about the completeness, reliability and accuracy of this information. Any action you take upon the information you find here, is strictly at your own risk. We are not be liable for any losses and/or damages in connection with the use of this information.

While we strive to make the information as accurate as possible, we make no claims, promises, or guarantees about its accuracy, completeness, or adequacy. We expressly disclaim liability for content, errors and omissions in this information.

Let’s dig in.

Getting started

In June, Collabora procured an International edition of the Samsung Galaxy S21 phone, powered by a system-on-chip with Mali G78. Although Arm announced Valhall with the Mali G77 in May 2019, roll out has been slow due to the COVID-19 pandemic. At the time of writing, there are not yet Linux friendly devices with a Valhall chip, forcing use of a locked down Android device. There’s a silver lining: we have a head start on the reverse-engineering, so by the time hacker-friendly devices arrive with Valhall GPUs, we can have open source drivers ready.

Android complicates reverse-engineering (though not as much as macOS). On Linux, we can compile a library on the device to intercept data sent to the GPU. On Android, we must cross-compile from a desktop with the Android Native Development Kit, ironically software that doesn’t run on Arm processors. Further, where on Linux we can track the standard system calls, Android device drivers replace the standard open() system call with a complicated Android-only “binder” interface. Adapting the library to support binder would be gnarly, but do we have to? We could sprinkle in one little hack anywhere we see a file descriptor without the file name.

#define MALI0 "/dev/mali0"

bool is_mali(int fd)
{
    char in[128] = { 0 }, out[128] = { 0 };
    snprintf(in, sizeof(in), "/proc/self/fd/%d", fd);

    int count = readlink(in, out, sizeof(out) - 1);
    return count == strlen(MALI0) && strncmp(out, MALI0, count) == 0;
}

Now we can hook the Mali ioctl() calls without tracing binder and easily dump graphics memory.

We’re interested in the new instruction set, so we’re looking for the compiled shader binaries in memory. There’s a chicken-and-egg problem: we need to find the shaders to reverse-engineer them, but we need to reverse-engineer the shaders to know what to look for. Fortunately, there’s an escape hatch. The proprietary Mali drivers allow an OpenGL application to query the compiled binary with the ARM_mali_program_binary extension, returning a file in the Mali Binary Shader format. That format was reverse-engineered years ago by Connor Abbott for earlier Mali architectures, and the basic structure is unchanged in Valhall. Our task is simple: compile a test shader, dump both GPU memory and the Mali Binary Shader, and find the common section. Searching for the common bytes produces an address in executable graphics memory, in this case 0x7f0002de00. Searching for that address in turn finds the “shader program descriptor” which references it.

18 00 00 80 00 10 00 00 00 DE 02 00 7F 00 00 00

Another search shows this descriptor’s address in the payload of an index-driven vertex shading job for graphics or a compute job for OpenCL. Those jobs contain the Job Manager header introduced a decade ago for Midgard, so we understand them well: they form a linked list of jobs, and only the first job is passed to the kernel. The kernel interface has a “job chain” parameter on the submit system call taking a GPU address. We understand the kernel interface well as it is open source due to kernel licensing requirements.

Submit; Job Headers; Shader Program Descriptor; Shader

With each layer identified, we teach the wrapper library to chase the pointers and dump every shader executed, enabling us to reverse-engineer the new instruction set and develop a disassembler.

Instruction set reconnaissance

Reverse-engineering in the dark is possible, but it’s easier to have some light. While waiting for the Valhall phone to arrive, I read everything Arm made public about the instruction set, particularly this article from Anandtech. Without lifting a finger, that article tells us Valhall is…

  • Warp-based, like Bifrost, but with 16 threads per warp instead of Bifrost’s 4/8.
  • Isomorphic to Bifrost on the instruction level (“operational equivalence”).
  • Regularly encoded.
  • Flat, lacking Bifrost’s clause and tuple packaging.

It also says that Valhall has a 16KB instruction cache, holding 2048 instructions. Since Valhall has a regular encoding, we divide 16384 bytes by 2048 instructions to find a Valhall instruction is 8 bytes. Our first attempt at a “disassembler” can print hex dumps of every 8 bytes on a line; our calculation ensures that is the correct segmentation.

From here on, reverse-engineering is iterative. We have a baseline level of knowledge, and we want to grow that knowledge. To do so, we input test programs into the proprietary driver to observe the output, then perturbe the input program to see how the output changes.

As we discover new facts about the architecture, we update our disassembler, demonstrating new knowledge and separating the known from the unknown. Ideally, we encode these facts in a machine-readable file forming a single reference for the architecture. From this file, we can generate a disassembler, an assembler, an instruction encoder, and documentation. For Valhall, I use an XML file, resembling Bifrost’s equivalent XML.

Filling out this file is usually straightforward though tedious. Modern APIs are large, so there is a great deal of effort required to map the API requirements to the hardware features.

However, some hardware features do not map to any API. Here are subtler tales from reversing Valhall.

Dependency slots

Arithmetic is faster than memory access, so modern processors execute arithmetic in parallel with pending memory accesses. Modern GPU architectures require the compiler to manage this mechanism by analyzing the program and instructing the hardware to wait for the results before they’re needed.

For this purpose, Bifrost uses an explicit scoreboarding system. Bifrost groups up to 16 instructions together in a clause, and each clause has a fixed header. The compiler assigns a “dependency slot” between 0 and 7 to each clause, specified in the header. Each clause can wait on any set of slots, specified with another 8-bits in the clause header. Specifying dependencies per-clause is a compromise between precision and code size.

We expect Valhall to feature a similar scheme, but Valhall doesn’t have clauses or clause headers, so where does it specify this info?

Studying compiled shaders, we see the last byte of every instruction is usually zero. But when the result of a memory access is first read, the previous instruction has a bit set in the last byte. Which bit is set depends on the number of memory accesses in flight, so it seems the last byte encodes a dependency wait. The memory access instructions themselves are often zero in their last bytes, so it doesn’t look like the last byte is used to encode the dependency slot – but executing many memory access instructions at once and comparing the bits, we see a single 2-bit field stands out as differing. The dependency slot is specified inside the instruction, not in the metadata.

What makes this design practical? Two factors.

One, only the waits need to be specified in general. Arithmetic instructions don’t need a dependency slot, since they complete immediately. The longest message passing instructions is shorter than the longer arithmetic instruction, so there is space in the instruction itself to specify only when needed.

Two, the performance gain from adding extra slots levels off quickly. Valhall cuts back on Bifrost’s 8 slots (6 general purpose). Instead it has 4 or 5 slots, with only 3 general purpose, saving 4-bits for every instruction.

This story exemplifies a general pattern: Valhall is a flattening of Bifrost. Alternatively, Bifrost is “Valhall with clauses”, although that description is an anachronism. Why does Bifrost have clauses, and why does Valhall remove them? The pattern in this story of dependency waits generalizes to answer the question: grouping many instructions into Bifrost clauses allows the hardware to amortize operations like dependency waits and reduce the hardware gate count of the shader core. However, clauses add substantial encoding overhead, compiler complexity, and imprecision. Bifrost optimizes for die space; Valhall optimizes for performance.

The missing modifier

Hardware features that are unused by the proprietary driver are a perennial challenge for reverse-engineering. However, we have a complete Bifrost reference at our disposal, and Valhall instructions are usually equivalent to Bifrost. Special instructions and modes from Bifrost cast a shadow on Valhall, showing where there are gaps in our knowledge. Sometimes these gaps are impractical to close, short of brute-forcing the encoding space. Other times we can transfer knowledge and make good guesses.

Consider the Cross Lane PERmute instruction, CLPER, which takes a register and the index of another lane in the warp, and returns the value of the register in the specified lane. CLPER is a “subgroup operation”, required for Vulkan and used to implement screen-space derivatives in fragment shaders. On Bifrost, the CLPER instruction is defined as:

<ins name="+CLPER.i32" mask="0xfc000" exact="0x7c000">
  <src start="0" mask="0x7"/>
  <src start="3"/>
  <mod name="lane_op" start="6" size="2">
    <opt>none</opt>
    <opt>xor</opt>
    <opt>accumulate</opt>
    <opt>shift</opt>
  </mod>
  <mod name="subgroup" start="8" size="2">
    <opt>subgroup2</opt>
    <opt>subgroup4</opt>
    <opt>subgroup8</opt>
  </mod>
  <mod name="inactive_result" start="10" size="4">
    <opt>zero</opt>
    <opt>umax</opt>
    ....
    <opt>v2infn</opt>
    <opt>v2inf</opt>
  </mod>
</ins>

We expect a similar definition for Valhall. One modification is needed: Valhall warps contain 16 threads, so there should be a subgroup16 option after subgroup8, with the natural binary encoding 11. Looking at a binary Valhall CLPER instruction, we see a 11 pair corresponding to the subgroup field. Similarly experimenting with different subgroup operations in OpenCL lets us figure out the lane_op field. We end up with an instruction definition like:

<ins name="CLPER.u32" title="Cross-lane permute" dests="1" opcode="0xA0" opcode2="0xF">
  <src/>
  <src widen="true"/>
  <subgroup/>
  <lane_op/>
</ins>

Notice we do not specify the encoding in the Valhall XML, since Valhall encoding is regular. Also notice we lack the inactive_result modifier. On Bifrost, inactive_result specifies the value returned if the program attempts to access an inactive lane. We may guess Valhall has the same mechanism, but that modifier is not directly controllable by current APIs. How do we proceed?

If we can run code on the device, we can experiment with the instruction. Inactive lanes may be caused by divergent control flow, where one lane in the thread branches but another lane does not, forcing the hardware to execute only part of the warp. After reverse-engineering Valhall’s branch instructions, we can construct a situation where a single lane is active and the rest are inactive. Then we insert a CLPER instruction with extra bits set, store the result to main memory, and print the result. This assembly program does the trick:

# Elect a single lane
BRANCHZ.reconverge.id lane_id, offset:3

# Try to read a value from an inactive thread
CLPER.u32 r0, r0, 0x01000000.b3, inactive_result:VALUE

# Store the value
STORE.i32.slot0.reconverge @r0, u0, offset:0

# End shader
NOP.return

With the assembler we’re writing, we can assemble this compute kernel. How do we run it on the device without knowing the GPU data structures required to dispatch compute shaders? We make use of another classic reverse-engineering technique: instead of writing the initialization code ourselves, piggyback off the proprietary driver. Our wrapper library allows us to access graphics memory before the driver submits work to the hardware. We use this to read the memory, but we may also modify it. We already identified the shader program descriptor, so we can inject our own shaders. From here, we can jury-rig a script to execute arbitrary shader binaries on the device in the context of an OpenCL application running under the proprietary driver.

Putting it together, we find the inactive_result bits in the CLPER encoding and write one more script to dump all values.

for ((i = 0 ; i < 16 ; i++)); do
  sed -e "s/VALUE/$i/" shader.asm | python3 asm.py shader.bin
  adb push shader.bin /data/local/tmp/
  adb shell 'PANWRAP_SHADER_REPLACE=/data/local/tmp/shader.bin '\
    'LD_PRELOAD=/data/local/tmp/panwrap.so '\
    '/data/local/tmp/test-opencl'
done

The script’s output contains sixteen possibilities – and they line up perfectly with Bifrost’s sixteen options. Success.

Next steps

There’s more to learn about Valhall, but we’ve reverse-engineered enough to develop a Valhall compiler. As Valhall is a simplification of Bifrost, and we’ve already developed a free and open source compiler for Bifrost, this task is within reach. Indeed, adapting the Bifrost compiler to Valhall will require refactoring but little new development.

Mali G78 does bring changes beyond the instruction set. The data structures are changed to reduce Vulkan driver overhead. For example, the monolithic “Renderer State Descriptor” on Bifrost is split into a “Shader Program Descriptor” and a “Depth Stencil Descriptor”, so changes to the depth/stencil state no longer require the driver to re-emit shader state. True, the changes require more reverse-engineering. Fortunately, many data structures are adapted from Bifrost requiring few changes to the Mesa driver.

Overall, supporting Valhall in Mesa is within reach. If you’re designing a Linux-friendly device with Valhall and looking for open source drivers, please reach out!

 

Comments (7)

  1. Luke:
    Jul 21, 2021 at 06:38 AM

    Seems there is a mistake here:

    snprintf(sizeof(in) - 1, "/proc/self/fd/%d", fd);

    The signature of this function is

    int snprintf(char *str, size_t size, const char *format, ...);

    Reply to this comment

    Reply to this comment

    1. Alyssa Rosenzweig:
      Jul 22, 2021 at 05:17 PM

      Fixed, thank you for reading!

      Reply to this comment

      Reply to this comment

  2. Iman:
    Jul 22, 2021 at 04:27 PM

    awesome! 2 questions:
    1) does the device has to be rooted?
    2) how did you dump gpu memory?

    Reply to this comment

    Reply to this comment

    1. Alyssa Rosenzweig:
      Jul 22, 2021 at 05:19 PM

      To dump GPU memory, we hook the ioctl() system calls that map GPU memory into the CPU address space. By keeping track of the result of this call from the kernel, we get a mapping from GPU addresses to CPU addresses. Then we can just dump memory like it's any other buffer.

      The device does not have to be rooted for this. Indeed I haven't figured out how to root the phone I have, and not for lack of trying...

      Reply to this comment

      Reply to this comment

  3. Jon:
    Jul 26, 2021 at 07:27 PM

    Excellent work. Bravo!

    At some point I do hope ARM holdings starts publishing specs so people can work on making drivers better instead of having to reverse things. In the meantime, your work is a light in the darkness.

    Reply to this comment

    Reply to this comment

  4. Monarch Innovation Private Limited:
    Aug 05, 2021 at 07:34 AM

    Nice article about Reverse Engineeringand very good information really very useful for the engineer.

    Reply to this comment

    Reply to this comment

  5. Diego33:
    Aug 07, 2021 at 11:34 AM

    Hey! Thanks! Awesome resources. I would like to know if your compilator/decompilation would works properly on S20 (bifrost). I expect a lot has changed from Midgard to Valhall from Bifrost. I am actually looking forward hacking a few things with a bifrost assembly. Thanks!

    Reply to this comment

    Reply to this comment


Add a Comment






Allowed tags: <b><i><br>Add a new comment:


 

Search the newsroom

Latest News & Events

Integrating kernels and minds at the Linux Foundation Member Summit

15/11/2024

The Linux Foundation Member Summit is an opportune time to gather on the state of open source. Our talk will address the concerns and challenges…

Hello, MediaTek Genio!

14/11/2024

Today, we are delighted to announce a growing collaboration with MediaTek which will enable Collabora to introduce, improve, and maintain…

electronica 2024 with Renesas

06/11/2024

Join us at electronica 2024! In partnership with Renesas, Collabora will be showcasing GStreamer open source AI video analytics on the Renesas…

Open Since 2005 logo

Our website only uses a strictly necessary session cookie provided by our CMS system. To find out more please follow this link.

Collabora Limited © 2005-2024. All rights reserved. Privacy Notice. Sitemap.