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There are substantial challenges in building secure and safe systems on multicore processors (MCPs). Last level cache contention is undoubtedly the largest source of multicore interference, and a significant challenge for real-time systems. Here we discuss a proposed solution, called cache coloring. Opinions on cache coloring are mixed, sometimes extreme, and the implementation can be difficult and risky. This article aims to demystify cache coloring by clarifying exactly how it works. We hope that the example using a real Intel processor and accurate diagrams allows you to grasp cache coloring without getting lost in lines, sets and ways.


First, a word about who we are. Lynx Software Technologies has built and supported real-time operating systems (RTOSes) since 1988. We have witnessed hardware and embedded software technologies evolve and have supported our customers through the design, development, integration, certification, deployment, and support of software systems across mission-critical applications in AVIONICS, INDUSTRIAL, AUTOMOTIVE, UNMANNED SYSTEMS, DEFENSE, SECURE LAPTOPS, CRITICAL INFRASTRUCTURE, and other markets. In this article, we discuss various approaches to cache coloring to reduce multicore interference, including cache coloring via the memory management unit, an RTOS, a hypervisor, and finally, via hardware.


RTOS vendors are beginning to react to the biggest source of multicore interference – last level cache contention. In a multicore processor, the last level cache (LLC) is shared by all cores and means that a noisy neighbor can have a drastic impact on the worst-case execution time (WCET) of software on other cores. Researchers Bechtel and Yun achieved a slowdown factor of 3401 using adversarial benchmarks. The slowdown swamps the theoretical 4X speedup expected from a quad core MCP, for example.

What is cache coloring?

Cache coloring is a clever software-only approach to cache partitioning. Modern processors use a set associative cache architecture that is a balance between the simplicity of a direct mapped cache and the silicon cost of a fully associative cache. A side-effect of set associative caches is that only a small number of cache lines, those which reside a multiple of the set size apart, can co-exist in the cache. In normal operation, this is an unavoidable limitation of the cache that slightly reduces the hit rate (by approximately 2%)2. When designing new processors, semiconductor vendors conduct simulations and carefully choose the cache set size for optimal performance on average. But, if you are clever, this artifact can be used to deliberately divide memory into regions that cannot evict each other from cache. Effectively, to partition the cache artificially.

Cache coloring on Ice Lake

For example, the Intel Core i7-1065G7 (Ice Lake) processor3 launched in Q3 2019 is a quad core chip with 3 cache levels. Its last level cache is L3. This cache is 8MB in size, with 64 bytes per line and is 16-way set associative. The cache always deals in line-sized chunks; that is, the smallest block of memory that can be cached is 64-bytes. 16-way set associative means that the 8MB cache is divided up into 16 duplicate 512KB (8192 line) chunks called ways. A cache way fits over memory like a window repeating exactly every 512KB. Lines have fixed positions within the way, so, the first line can only store a single line, (the first one) out of every 512KB block of memory.

Fig. 1 Intel Core i7-1065G7 8MB 16-way set associative L3 cache.

The effect of this is that out of the thousands4 of first lines, repeating every 512KB through memory, any 16 can be simultaneously cached. If an application can arrange to exclusively use only those 512KB-apart 64-byte-long memory stripes, that memory effectively forms a tiny private 1024-byte (16 line long) cache.

Fig. 2 Memory lines cacheable by first cache line. Inconvenient for programming.

Writing code that uses memory striped like a venetian blind is incredibly inconvenient. Malloc could be modified to automatically provide memory from stripes, and that could allow variables to be cache partitioned, but it does not help cache partition your code. To make this practical, a way to combine the stripes into contiguous blocks that can be treated like normal memory is needed.

Cache coloring using MMU

As it happens, we already have an efficient and practical way to map memory—the Memory Management Unit (MMU). It can take 4K memory pages, sprinkled from anywhere in memory and map them into one or many contiguous memory blocks. The only snag is that 4K pages are too big for our 64-byte lines. This can be overcome, however, by combining 64 of the 64-byte cache lines together to fill the 4K page (64 X 64-bytes = 4K). Instead of 8192 tiny 1K caches, this gives us 128 larger 64K caches. This approach is called cache coloring. We have built 128 “colors” in memory. If an application has exclusive access to, and stays within its own color then it has its own private subset of the L3 cache. Colors can be combined, to provide larger (but fewer) cache partitions. Combinations of large and small partitions are also possible as long as they are a) a multiple of 4K and b) less than 4MB5 in size.

TL- Fig 03-fina

Fig. 3 (left) Cache lines grouped into MMU pages and mapped into contiguous blocks of memory.

Problems with cache coloring

Ultimately, cache coloring partially defeats how the cache was designed to operate. The utility of the cache has been diluted by reducing the flexibility of which parts of memory can be cached. The average performance of the entire system will be lower using cache coloring, but cache contention will be reduced and determinism improved. For real-time systems, this should be an overall win, yet the cache coloring concept is a kind of hack that uses the CPU in an unintended way, likely leaving users on their own should they need help with cache coloring from their semiconductor vendor.

Cache coloring suffers from a number of difficulties that, while not insurmountable, make it difficult and risky for RTOS vendors to implement. For one, cache coloring is specific to the cache structure of your CPU. The cache size and number of ways vary depending on the model of your Intel, Arm, or PowerPC CPU. An intelligent implementation could be written to be portable—that is, to sense, adjust and cope with different cache parameters—but the task is not easy. Additionally, future cache architectures may depart from the linear mapping of lines and instead use something like a hash table, which may be hidden or undocumented and could make the reverse engineering necessary to implement cache coloring impossible. Lastly, cache coloring has a large impact on the internal structure of an RTOS. Such an RTOS likely already has memory regions assigned for kernel space, drivers, processes, shared memory, io, ramdisk, ARINC partitions, stack, heap etc. Fitting cache partitioning in so that it co-exists with all that will be a big upheaval and may require compromises in other areas.


Linus on cache coloring

Linus Torvalds is strongly against cache coloring for Linux. In this 2003 Linux kernel mailing list discussion with Anton Ertl from the Vienna University of Technology he argues against cache coloring:

“Also, the work has been done to test things, and cache coloring definitely makes performance _worse_. It does so exactly because it artificially limits your page choices, causing problems at multiple levels (not just at the cache, like this example, but also in page allocators and freeing). So basically, cache coloring results in:

–some nice benchmarks (mainly the kind that walk memory very predictably, notably FP kernels)
–mostly worse performance in "real life"
–more complex code
–much worse memory pressure

My strong opinion is that it is worthless except possibly as a performance tuning tool, but even there the repeatability is a false advantage: if you do performance tuning using cache coloring, there is nothing that guarantees that your tuning was _correct_ for the real world case.”

He states later, in the same thread:

“The real degradation comes in just the fact that cache coloring itself is often expensive to implement and causes nasty side effects like bad memory allocation patterns, and nasty special cases that you have to worry about (ie special fallback code on non-colored pages when required). That expense is both a run-time expense _and_ a conceptual one (a conceptual expense is something that complicates the internal workings of the allocator so much that it becomes harder to think about and more bugprone). So far nobody has shown a reasonable way to do it without either of the two.”

And, later still:

“Hey, there have been at least four different major cache coloring trials for the kernel over the years. This discussion has been going on since the early nineties. And _none_ of them have worked well in practice.”

Cache coloring using a hypervisor

Instead of implementing cache coloring in an RTOS, a hypervisor implementation is more elegant. A hypervisor is already using the MMU to map RAM to create guest virtual machines. This is not the regular MMU, but second level address translation (SLAT) provided by the MCP hardware specifically to support virtualization. Intel’s SLAT is called EPT, Extended Page Tables, Arm’s implementation is the Stage-2 MMU. SLAT provides nested MMU paging that allows the hypervisor, running in privileged mode, to map physical memory to create virtual machines. The trick is that those virtual machines have their own MMU, and use it as normal from their own kernel space to create their own (MMU protected as normal) user processes. A guest OS running in this type of virtualized environment is oblivious to the presence of the hypervisor.

A hypervisor’s use of the MMU, “just” to create virtual machines is relatively simple compared with an RTOS. Implementing cache coloring in the hypervisor would be a cleaner approach. The messy mapping of memory stripes would be contained in hypervisor space and completely normal memory presented to guests - a clean and elegant approach that would allow unmodified guest OSs to benefit from cache coloring automatically.

Lynx’s preferred alternative: Hardware cache partitioning

In the last 5 years the major architectures, x86, Arm and PowerPC, have all implemented hardware cache partitioning. Lynx prefers hardware cache partitioning over cache coloring. In our opinion a simple, efficient and officially supported hardware feature is low risk vs any cache coloring implementation.

Cache partitioning on Intel Xeon E5

Intel first implemented hardware cache partitioning in their Intel Xeon E5-2600 v3 family of server processors in November 2016, and following that it is present in all Xeon chips beginning with the Xeon E5 v4 family. Intel’s hardware cache partitioning is called Cache Allocation Technology (CAT) and is part of Intel’s wider Resource Director Technology (RDT) suite. With the latest generation of Intel processors CAT has trickled down and is now present in Atom chips. Intel’s CAT implementation defines a CBM, Capacity Bitmask, register that divides up the LLC. A chip that reports a cache Capacity Bitmask of 16 allows the LLC to be divided into sixteenths. For example, the Atom C3958 released August 2017 has a CBM of 4, the earlier Xeon D-1541 from 2015 has a CBM of 16. The LynxSecure Separation Kernel hypervisor has supported Intel CAT since 2019.

NXP also has a hardware cache partitioning implementation in the e6500 PowerPC cores6. The e6500-based QorIQ T2080 was released in 2014 and has a 2MB L2 last level cache that is 16-way set associative with a 64-byte line size. LynxSecure supports PowerPC hardware cache partitioning in our beta release for the T2080. NXP defines a set of registers, L2PIR, L2PAR and L2PWR, that allow cache ways to be selectively disabled with the result that the LLC can be divided into sixteenths.

Arm added hardware cache partitioning with Armv8.4-A architecture in 2017. That is, the application variant of Armv8.4. Arm’s hardware cache partitioning is part of their Memory Partitioning and Monitoring (MPAM) extension. LynxSecure does not yet support hardware cache partitioning on Arm.

State of the industry

It is difficult to find the precise status of cache coloring support in the embedded industry. One suspects support for this relatively new feature is sparse. RTOS vendors are naturally cautious talking to their competitors, especially about new features they are lacking. However, DDC-I have a feature called “memory pools” in their RTOS that looks like cache coloring. It is a portable software implementation that provides cache partitioning. DDC-I have 4 patents dating from 2008 that cover “cache pooling”, but I doubt that RTOS vendors are avoiding cache coloring due to the DDC-I patents. Enforcing them would be interesting given the number of cache coloring references that predate 2008. Greenhills have something called Bandwidth Allocation and Monitoring (BAM) announced in 2020, however, from public sources it is difficult to discern what BAM is in any detail.

Cache partitioning is valuable for real-time systems, but there is much more to multicore interference than just LLC contention. There are pros and cons to both cache coloring and hardware cache partitioning, but both have their place. Hopefully this article was useful to make an informed decision about types of cache partitioning.

Multicore safety is an area of expertise and active innovation for Lynx Software Technologies. Multicore designs should be approached with caution and careful planning to understand the complexity and minimize risks. Our experience is that there are large pitfalls and no easy solutions. We are engaged in several multicore avionics design and research projects and would be delighted to discuss multicore safety and partitioning strategies for your next project. As ever, Lynx Software is at your service and would be delighted to discuss your next project and any multicore, safety or partitioning features you require.



  1. Bechtel & Yun, Denial-of-Service Attacks on Shared Cache in Multicore: Analysis and Prevention, IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS), April 2019.
  2. Fig 5.16 on page 407 of Hennessy & Patterson, Computer Oganization and Design The Hardware/Software Interface – 5th ed. Morgan-Kaufman, 1998.
  3. Intel Ice Lake L3 cache size.
  4. 16,384 in a computer with a typical 8GB of memory installed
  5. The product number of colors X color size must be 8MB or less. The extreme case is 2 colors of 4MB each
  6. NXP e6500 Core Reference Manual section, L2 cache partitioning
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