Out-of-Memory is (Usually) a Lie

• The most common exception logged by Fiddler telemetry is OutOfMemoryException.
• Yesterday, a Facebook friend lamented: “How does firefox have out of memory errors so often while only taking up 1.2 of my 8 gigs of ram?”
• This morning, a Python script running on my machine as a part of the Chromium build process failed with a MemoryError, despite 22gb of idle RAM.

Most platforms return an “Out of Memory error” if an attempt to allocate a block of memory fails, but the root cause of that problem very rarely has anything to do with truly being “out of memory.” That’s because, on almost every modern operating system, the memory manager will happily use your available hard disk space as place to store pages of memory that don’t fit in RAM; your computer can usually allocate memory until the disk fills up (or a swap limit is hit; in Windows, see System Properties > Performance Options > Advanced > Virtual memory).

So, what’s happening?

In most cases, the system isn’t out of RAM—instead, the memory manager simply cannot find a contiguous block of address space large enough to satisfy the program’s allocation request.

In each of the failure cases above, the process was 32bit. It doesn’t matter how much RAM you have, running in a 32bit process nearly always means that there are fewer than 3 billion addresses¹ at which the allocation can begin. If you request an allocation of n bytes, the system must have n unused addresses in a row available to satisfy that request.

Making matters much worse, every active allocation in the program’s address space can cause “fragmentation” that can prevent future allocations by splitting available memory into chunks that are individually too small to satisfy a new allocation with one contiguous block.

Running out of address space most often occurs when dealing with large data objects like arrays; in Fiddler, a huge server response like a movie or .iso download can be problematic. In my Python script failure this morning, a 1.3gb file (chrome_child.dll.pdb) needed to be loaded so its hash could be computed. In some cases, restarting a process may resolve the problem by either freeing up address space, or by temporarily reducing fragmentation enough that a large allocation can succeed.

Running 64-bit versions of programs will usually eliminate problems with address space exhaustion, although you can still hit “out-of-memory” errors before your hard disk is full. For instance, to limit their capabilities and prevent “runaway” allocations, Chrome’s untrusted rendering processes run within a Windows job object with a 4gb memory allocation limit:

Elsewhere, the .NET runtime restricts individual array dimensions to 2^31 entries, even in 64bit processes².

-Eric Lawrence

¹ If a 32bit application has the LARGEADDRESSAWARE flag set, it has access to s full 4gb of address space when run on a 64bit version of Windows.

² So far, four readers have written to explain that the gcAllowVeryLargeObjects flag removes this .NET limitation. It does not. This flag allows objects which occupy more than 2gb of memory, but it does not permit a single-dimensional array to contain more than 2^31 entries.