Boost Rust Performance: New Bit Compression & Expansion

Hey there, fellow Rustaceans! 👋 Ever found yourself wrestling with bit-level operations in Rust, trying to squeeze every last drop of performance out of your code? If so, you're in for a treat, because we're about to dive into a super exciting proposal that could dramatically boost how we handle bit manipulation in our favorite language. We're talking about adding compress_bits and expand_bits functions directly to Rust's unsigned integers. Think of it: a cleaner, faster, and more efficient way to pack and unpack bits, leveraging those awesome hardware capabilities most of us don't even know exist or how to access!

For a long time, working with individual bits or specific groups of bits within an integer often meant writing intricate sequences of shifts, masks, and logical operations. While perfectly functional, these naive software implementations often leave a lot of performance on the table. Why? Because modern CPUs are packed with specialized instructions designed specifically for these kinds of tasks – instructions that can do in a single cycle what our multiple lines of Rust code might take many cycles to achieve. This proposal aims to bridge that gap, giving us, the developers, direct access to these powerful underlying mechanisms through simple, intuitive functions in the standard library. Imagine simplifying complex bit-juggling into a single, optimized function call! This isn't just about micro-optimizations; it's about enabling a whole new class of efficient algorithms and data structures in Rust, making our code not just correct, but blazingly fast by default. So, grab your favorite beverage, and let's unravel why bit compression and expansion are such game-changers for Rust.

The Hidden Performance Drain: Why Current Bit Manipulation Falls Short

Alright, guys, let's get real about the current state of bit manipulation in Rust. When we need to extract specific bits from an integer or deposit them into a new one according to a mask (think of a mask as a blueprint telling you which bits to care about), what do we usually do? We write a loop, we shift, we mask, we OR, and we rinse and repeat. It's a completely valid approach, and it works, but here’s the kicker: it’s often far from optimal. The biggest issue here is that there's currently no direct way to automatically leverage the incredibly powerful compiler optimizations or specialized hardware instructions that are literally built into our CPUs for these exact operations.

Imagine you have a u32 and you only care about the 3rd, 5th, and 7th bits. To pull those out and pack them into the least significant bits of a new integer, you'd write a sequence of operations. This "naive implementation," while functionally correct, means your compiler has to generate generic machine code that executes these shifts and masks one by one. It doesn't know that you're trying to do a specific, common bit-shuffling operation that a CPU like an Intel Haswell (or newer) or an ARM SVE2 chip could do in a single instruction. These specialized instructions, often referred to as parallel bit extract/deposit, gather/scatter, or compress/expand operations, are designed for exactly this kind of task, offering significant performance gains – sometimes orders of magnitude faster than a software loop.

The problem compounds because implementing these operations efficiently in a portable way is incredibly non-trivial. You could write assembly, or use platform-specific intrinsics, but that ties your code to a specific architecture, making it much harder to maintain and less accessible to the wider Rust ecosystem. Without a standard library abstraction, developers are forced to either accept suboptimal performance from naive Rust code, or delve into the messy world of conditional compilation, #[cfg] attributes, and unsafe blocks just to get to those juicy hardware instructions. This creates a barrier to entry for many common algorithms and data structures that rely heavily on efficient bit manipulation. We're essentially leaving free performance on the table, and that's just not very Rusty, is it? This proposal aims to solve this by providing first-class, optimized support for these fundamental bit operations, making high-performance bit twiddling a breeze for everyone. This is a crucial step towards making Rust an even more powerful language for low-level systems programming and high-performance computing, ensuring that our code runs as fast as the hardware allows, without us having to become assembly wizards.

Understanding compress_bits and expand_bits

Let's quickly define what we're talking about with compress_bits and expand_bits.

• compress_bits(value, mask): Think of this as a "bit vacuum cleaner." It takes all the bits in value that correspond to 1s in the mask, and then packs them tightly into the least significant bits of a new result. All the other bits are discarded. It's like taking a sparse set of items and arranging them contiguously.

  Example: If value is 0b1011_1100 and mask is 0b0010_0100:

  • The mask says "grab the 3rd bit from the right and the 6th bit from the right."
  • The 3rd bit of value is 1. The 6th bit of value is 0.
  • So, compress_bits would pack 01 (from right to left: 3rd bit, then 6th bit) into 0b0000_0011. Pretty neat, right?

• expand_bits(value, mask): This is the opposite – a "bit distributor" or "bit expander." It takes the least significant bits from value and distributes them to the positions specified by the 1s in the mask. All other bit positions in the result will be zero. It's like taking a compact list of items and scattering them to specific slots.

  Example: If value is 0b1010_1101 and mask is 0b0101_0101:

  • The mask says "put bits into the 1st, 3rd, 5th, and 7th positions from the right."
  • value's least significant bits (from right to left) are 1, 0, 1, 1.
  • expand_bits would take these and place them: 0b0101_0001. See how the 1, 0, 1, 1 from value got placed into the mask's positions?

These operations are incredibly versatile, and once you see them in action, you'll realize just how much heavy lifting they can do in various algorithms.

Why These Functions Matter: Unlocking New Possibilities and Performance

Now that we know what compress_bits and expand_bits do, let's talk about why they are such a big deal and why they absolutely deserve a spot in Rust's standard library. Guys, these aren't just obscure academic curiosities; they are fundamental building blocks for some really cool and super-efficient algorithms and data structures that we use every day, often without even realizing it. Integrating these functions directly into std means everyone gets access to highly optimized versions, taking advantage of hardware instructions without having to become an expert in low-level CPU architectures.

Think about variable-length encodings (like varints or certain Unicode representations). These often involve packing data into the fewest possible bits, or carefully extracting data from a stream where the length isn't fixed. compress_bits can be incredibly useful for efficiently extracting only the relevant data bits, while expand_bits can help in constructing these variable-length fields with minimal overhead. It streamlines the process, making parsers and serializes significantly faster and simpler to write. Another fantastic use case is bit interleaving and de-interleaving, famously used in Morton codes or other space-filling curves. Imagine you have 2D coordinates (X, Y) and you want to combine them into a single 1D index that preserves locality. You do this by interleaving their bits: X0Y0X1Y1X2Y2... expand_bits makes interleaving a breeze, and compress_bits can quickly de-interleave them back into X and Y components. This is critical for spatial indexing, game development (think octrees/quadtrees), and even certain types of database optimizations.

These functions also shine brightly in areas like perfect hashing and building lookup tables. Sometimes, to create a highly efficient hash table or a compact lookup structure, you need to perform specific bit permutations to distribute keys evenly or to extract unique identifiers. compress_bits and expand_bits provide the primitive operations necessary to craft such custom permutations with remarkable efficiency. Furthermore, in parsing tasks, especially those dealing with binary protocols or custom data formats, you often encounter situations where you need to extract non-contiguous fields of bits. Instead of a messy series of shifts and masks for each field, a well-defined compress_bits call with the right mask can pluck out exactly what you need in one go.

Finally, let's not forget succinct data structures. These are data structures designed to use space close to the information-theoretic lower bound, often relying heavily on intricate bit-level operations. Examples include bit vectors, wavelet trees, and others used in bioinformatics or large-scale text processing. compress_bits and expand_bits become powerful tools for building and querying these structures efficiently, directly impacting memory usage and query times. The truth is, without std support, achieving optimal performance for these scenarios often means either reinventing the wheel with suboptimal software implementations or resorting to platform-specific intrinsics – which immediately makes your code less portable and harder for the average Rust developer to use. This proposal is about bringing portable, high-performance bit manipulation to everyone in the Rust community, making it easier to write world-class, efficient code right out of the box. It’s about empowering Rust developers to tackle complex problems with the best tools available, without unnecessary friction.

Diving Into the Solution: How It Works and Why It's Smart

So, how do we actually go about implementing these super cool compress_bits and expand_bits functions in Rust? The key here is to provide an implementation that is not just correct, but blazingly fast, ideally leveraging those specific CPU instructions we talked about earlier. Let's first look at what a basic, naive software implementation might look like – this helps us understand the problem before we appreciate the optimized solution.

Here are the basic conceptual implementations for u32 for compress_bits and expand_bits. These examples demonstrate the logic, but they are absolutely not what we want to end up with for production std code due to their inherent inefficiency in software:

/// Returns `self` with the bit locations specified by `mask` packed
/// contiguously into the least significant bits of the result.
/// ```
/// let n = 0b1011_1100;
///
/// assert_eq!(compress_bits(n, 0b0010_0100), 0b0000_0011);
/// assert_eq!(compress_bits(n, 0xF0), 0b0000_1011);
/// ```
pub const fn compress_bits(self_: u32, mask: u32) -> u32 {
    let mut result = 0;
    let mut i = 0; // Iterator for the full 32 bits
    let mut j = 0; // Iterator for packed bits in the result
    while i < u32::BITS {
        let mask_bit = (mask >> i) & 1; // Check if the i-th bit in mask is set
        result |= (mask_bit & (self_ >> i)) << j; // If mask bit is 1, take the self_ bit and place it at j
        j += mask_bit; // Only increment j if we actually packed a bit
        i += 1;
    }
    result
}

/// Returns a result with the least significant bits of `self` distributed to
/// the bit locations specified by `mask`.
/// ```
/// let n = 0b1010_1101;
///
/// assert_eq!(expand_bits(n, 0b0101_0101), 0b0101_0001);
/// assert_eq!(expand_bits(n, 0xF0), 0b1101_0000);
/// ```
pub const fn expand_bits(self_: u32, mask: u32) -> u32 {
    let mut result = 0;
    let mut i = 0; // Iterator for the full 32 bits of the result
    let mut j = 0; // Iterator for the least significant bits of self_
    while i < u32::BITS {
        let mask_bit = (mask >> i) & 1; // Check if the i-th bit in mask is set
        result |= (mask_bit & (self_ >> j)) << i; // If mask bit is 1, take the j-th bit from self_ and place it at i
        j += mask_bit; // Only increment j if we actually used a bit from self_
        i += 1;
    }
    result
}

These const fn implementations are straightforward, iterating through each bit, checking the mask, and then either packing or expanding the bits one by one. While const fn is a fantastic feature for compile-time computations, making these functions useful in const contexts, the loop structure here is what makes them inefficient at runtime. For every single bit, we're performing multiple operations: a shift, an AND, another shift, and an OR. Over 32 or 64 bits, this adds up to a significant number of CPU cycles. This is precisely the kind of busy work that modern hardware is designed to short-circuit.

The truly optimal way to implement these functions isn't with these explicit loops. Instead, it involves one of two primary approaches:

1. Bit Twiddling Hacks (Software Optimization): For platforms without native instructions, highly optimized software implementations exist. One famous technique involves an XOR parallel suffix algorithm, as extensively discussed in "Hacker's Delight" by Henry S. Warren Jr. These algorithms are incredibly clever, often transforming the bit-by-bit operations into a series of parallel bitwise operations that can run much faster than a simple loop. They typically involve multiple stages of masks and shifts to move bits into their correct places simultaneously.
2. Native Hardware Instructions: This is where the magic really happens! CPUs have evolved to include instructions specifically for these operations. On x86 architectures, we have PEXT (Parallel Bit Extract) and PDEP (Parallel Bit Deposit) as part of the BMI2 instruction set (introduced with Intel Haswell). On Arm SVE2, you'll find BEXT and BDEP. These instructions can perform the entire compress or expand operation on a 32-bit or 64-bit integer in a single CPU cycle. Imagine replacing tens of software instructions with just one! That's a massive win for performance!

The beauty of adding these to std is that the Rust compiler, specifically through LLVM, can be taught to recognize these patterns or directly use intrinsics (special compiler functions that map directly to hardware instructions) for PEXT/PDEP or BEXT/BDEP when targeting compatible platforms. If the mask is known at compile-time (e.g., a constant), the compiler can even optimize the operation down to just a few instructions, sometimes even fewer than the direct intrinsic might imply, by pre-calculating parts of the operation. This means we get the best of both worlds: a clear, semantic API in Rust, and the fastest possible execution on whatever hardware our code runs on, all handled automatically by the compiler. It’s a classic case of abstracting away complexity while delivering peak performance, which is exactly what Rust strives for.

Why Not Just Stick with Alternatives? The Case for std Inclusion

Okay, so we've seen how awesome compress_bits and expand_bits are, but a fair question to ask is: "Can't we just use alternatives?" The proposal itself mentions a couple: "Do nothing" or "Wait for LLVM to implement generic intrinsics." Let's break down why these alternatives, while seemingly viable, actually fall short and why including these functions directly in Rust's standard library is the optimal path forward.

First, let's consider "Do nothing" and rely on third-party crates. Sure, there are already crates out there that might implement these bit operations, either in pure software or by wrapping platform-specific intrinsics. But here's the problem, guys: relying solely on third-party crates introduces a whole host of issues. For starters, discoverability becomes a problem. New Rust developers, or even seasoned ones venturing into a new domain, might not know which crate to use, or even that such highly optimized functions exist. They'll likely default to the naive loop-based implementations, missing out on massive performance gains without even realizing it. Then there's portability and maintenance. A third-party crate might implement intrinsics for x86, but what about ARM? Or RISC-V? Maintaining cross-platform compatibility and ensuring all these implementations are correct and equally optimized across different architectures is a huge undertaking for individual crate authors. The standard library, backed by the Rust team, has the resources and expertise to ensure these functions are globally optimized and correct for all supported targets, taking advantage of #[cfg]s and compiler intrinsics where available, and providing robust software fallbacks otherwise. This standardization significantly reduces fragmentation and ensures a consistent high-performance baseline for everyone.

Second, the idea of "Waiting for LLVM to implement the intrinsic" sounds good on the surface. LLVM is the compiler backend for Rust, and if it could magically optimize any compress_bits-like pattern into a PEXT instruction, that would be amazing! However, this is a very optimistic and potentially very long-term solution. While there has been discussion around generic bit manipulation intrinsics in LLVM and even C++ proposals (like for C++26) to include such functionality, these things take years to standardize and implement across all compiler versions and targets. More importantly, relying solely on LLVM's pattern matching to detect and optimize these operations can be fragile. Compilers are smart, but they're not mind-readers. A slight variation in your Rust code might prevent the optimization from kicking in, leading to inconsistent performance. By providing explicit std functions, we give the compiler a clear signal that "this is a bit compression/expansion operation, go use the fastest possible method for this target." It removes ambiguity and ensures reliable, optimized code generation every single time.

Ultimately, putting compress_bits and expand_bits directly into std isn't just about convenience; it's about establishing best practices, guaranteeing high performance across the ecosystem, and empowering all Rust developers with tools that would otherwise be difficult or risky to integrate. It standardizes common, critical operations, making Rust code more performant, more readable, and more robust, without forcing developers to become experts in low-level CPU instruction sets or hunt for specialized crates. It’s about making the "pit of success" deeper for bit manipulation in Rust!

Naming Our New Bit-Bending Buddies: Clarity and Consistency

Picking the right names for new functions in the standard library is super important, guys. It's not just about what sounds cool, but about clarity, consistency, and avoiding ambiguity. The proposal throws out a few options for our new bit manipulation heroes:

1. compress_bits, expand_bits
2. gather_bits, scatter_bits
3. extract_bits, deposit_bits

Let's break these down.

First up, compress_bits and expand_bits. These are the names proposed as the preferred choice, and for good reason! "Compress" clearly conveys the idea of taking spread-out bits and packing them tightly together. You're compressing information. "Expand" is its perfect inverse: taking a compact set of bits and expanding them out to specific, sparser locations. These terms are intuitive, directly descriptive of the operation, and feel very natural. They don't have a lot of other overloaded meanings in common programming contexts, which is a huge plus for avoiding confusion. When you see compress_bits, you immediately get a mental image of bits squishing together.

Next, we have gather_bits and scatter_bits. These are also quite good! "Gather" definitely implies collecting things from different places, and "scatter" means distributing them. These names are often used in the context of vector operations (like gather and scatter instructions in SIMD), which is a nice parallel given that bit manipulation can sometimes feel like a very small-scale vector operation. However, "gather" and "scatter" can sometimes imply memory access patterns (gathering data from non-contiguous memory locations, scattering to them), which, while related to bit positions, might not be as directly descriptive of the bit-level packing/unpacking as "compress" and "expand." Still, they're strong contenders.

Finally, extract_bits and deposit_bits. The proposal specifically notes that "extract" is "too overloaded with meaning to be a good name for what it does." And honestly, that's a fair point. "Extract" could mean pulling out a contiguous block of bits, or shifting a single bit, or any number of things. It's a very generic term. While extract_bits might technically describe pulling bits out, it doesn't clearly convey the packing aspect. Similarly, "deposit" means placing something, but again, it doesn't quite capture the idea of expanding from a compact source to sparse locations as clearly as expand_bits does. In the context of hardware instructions (PEXT/PDEP), these names are common, but for a higher-level API in Rust, we want something that speaks to the human developer first.

Considering all this, the compress_bits and expand_bits pairing really stands out. They are clear, unambiguous, symmetrical, and descriptive. They align well with Rust's philosophy of making complex operations approachable and understandable, and will serve the community well for years to come.

The Wider World of Bit Manipulation: Where These Ideas Come From

It's always fascinating to see how common problems get solved across different computing landscapes, and our proposal for compress_bits and expand_bits is no exception. These aren't entirely new concepts; they have deep roots in both hardware design and various programming languages, underscoring their fundamental importance. Understanding this lineage helps us appreciate why bringing them to Rust std is such a valuable move.

Let's start with the hardware side, because that's where the real performance comes from. On x86 architectures, especially those built on Intel's Haswell microarchitecture and later, we have the BMI2 (Bit Manipulation Instruction Set 2). Within BMI2, there are two incredibly powerful instructions: PEXT (Parallel Bit Extract) and PDEP (Parallel Bit Deposit). PEXT is essentially our compress_bits – it takes a source operand and a mask, extracts the bits corresponding to the 1s in the mask, and packs them into the destination. PDEP is expand_bits – it takes bits from a source and deposits them into the destination wherever the mask has a 1. These instructions are lightning fast because they're executed directly by the CPU, often completing in a single clock cycle. Similarly, on Arm SVE2 (Scalable Vector Extension 2), you'll find equivalent instructions like BEXT and BDEP that perform exactly the same parallel bit extract and deposit operations, showcasing that this functionality is considered essential across major modern CPU architectures.

Beyond specialized hardware, these concepts have also appeared in high-level languages known for their powerful array and bit manipulation capabilities. For instance, the programming language APL (A Programming Language), famous for its concise notation and powerful array operations, has functions like "Replicate" and "Expand" that perform conceptually similar tasks, often involving manipulating elements based on a boolean mask. This shows that the need to selectively gather and scatter data (whether bits or other elements) is a recurring theme in efficient computation.

Furthermore, there's a rich history of bit twiddling hacks – clever software algorithms to perform these operations when dedicated hardware instructions aren't available or accessible. Resources like the "Hacker's Delight" book are goldmines for these, demonstrating how to use sequences of shifts and XORs to achieve bit permutations efficiently. The fact that the C++ standard is also looking to include similar functionality in C++26 (as seen in proposals like the "bit permutations" one) really emphasizes that this isn't just a niche Rust need; it's a widely recognized gap in standard library offerings across multiple high-performance languages.

All these pieces of related work highlight a clear trend: the ability to efficiently compress and expand bits is a fundamental primitive, recognized by CPU designers, language designers, and algorithm authors alike. Bringing compress_bits and expand_bits to Rust's std would align our language with the cutting edge of hardware capabilities and established best practices in high-performance computing, providing developers with robust, optimized tools right out of the box.

What's Next for This Proposal? Navigating the Rust Feature Lifecycle

So, we've laid out the problem, explained the awesome solution, and explored why compress_bits and expand_bits are essential additions to Rust. Now, you might be wondering, "What actually happens next?" Well, guys, this isn't just a casual chat; this is an official API Change Proposal (ACP), and it's part of the libs-api team feature lifecycle in Rust. It's a structured process to ensure that new additions to the standard library are well-thought-out, widely applicable, and align with Rust's overall philosophy.

Once an ACP like this is filed, it enters a review queue for the libs-api team. These are the folks who carefully evaluate proposed changes and additions to Rust's standard library. It's a thorough process, which means while response times don't have a clear estimate, it can sometimes take several months for a proposal to move through the pipeline. The team needs to consider many factors: the utility of the feature, its impact on the language's learnability, potential performance implications, alternative approaches, and how well it fits into the existing std ecosystem. This careful consideration is exactly what makes Rust's standard library so robust and high-quality!

The libs team's review process typically involves a couple of stages and possible responses:

First, they'll look at the problem itself. Even before diving into the specific solution, they'll ask:

• "Do we think this problem seems worth solving, and is the standard library the right place to solve it?" If the problem is deemed important enough and std is the best home for the solution, that's a big step forward!
• Conversely, they might decide, "We think that this probably doesn't belong in the standard library." This could be due to it being too niche, better suited for a dedicated crate, or perhaps solvable with existing primitives in an acceptable way.

If the problem is approved for std consideration, they'll then dive into the concrete solution proposed in the ACP:

• They might respond with: "We think this specific solution looks roughly right, approved, you or someone else should implement this." This is the green light! It means the core idea and its implementation sketch are solid, and actual coding can begin, followed by further review during the implementation Pull Request.
• Or, they might say: "We're not sure this is the right solution, and the alternatives or other materials don't give us enough information to be sure about that. Here are some questions we have that aren't answered, or rough ideas about alternatives we'd want to see discussed." This isn't a rejection, but an invitation for further discussion, clarification, and potentially refinement of the proposal. It's about ensuring the absolute best solution is chosen for the long-term health of the standard library.

This structured approach ensures that any new feature, like our bit compression and expansion functions, is thoroughly vetted before it becomes a permanent part of the Rust experience. It's a collaborative effort, and the community's input and discussion play a vital role in shaping the future of Rust!

Conclusion: Embracing Future-Proof Bit Manipulation in Rust

Whew, what a ride! We've explored the fascinating world of bit compression and expansion, delving into why these seemingly niche operations are actually critical for unlocking top-tier performance and simplifying complex algorithms in Rust. From optimizing variable-length encodings and Morton codes to powering succinct data structures and parsing tasks, the impact of compress_bits and expand_bits is truly far-reaching. By bringing these functions directly into Rust's standard library, we're not just adding new methods; we're providing a standardized, portable, and highly optimized gateway to modern CPU capabilities like PEXT/PDEP and BEXT/BDEP.

This proposal represents a significant step forward, promising to make Rust even more powerful for low-level systems programming and high-performance computing. It means less time wrestling with convoluted bitwise operations and more time focusing on building amazing, blazingly fast applications. The clarity of compress_bits and expand_bits as names, combined with the underlying compiler optimizations, will elevate the quality and efficiency of Rust code across the board. So, let's keep the discussion going, support this proposal, and help make Rust's bit manipulation capabilities truly future-proof and accessible to every developer. Your high-performance Rust applications will thank you!