Paper - 1999 USENIX Annual Technical Conference, June 6-11, 1999, Monterey, California, USA   
[Technical Program]
Pp. 85100 of the Proceedings | |
The Region Trap Library: Handling Traps on
Application-Defined Regions of Memory
Tim Brecht
Department of Computer Science
University of Waterloo, Waterloo, ON Canada
brecht@cs.uwaterloo.ca
Harjinder Sandhu
Department of Computer Science
York University, Toronto, ON Canada
hsandhu@cs.yorku.ca
Abstract:
User-level virtual memory (VM) primitives are used in many different
application domains including
distributed shared memory, persistent objects, garbage
collection, and checkpointing.
Unfortunately, VM primitives only allow traps to be handled at
the granularity of fixed-sized pages defined by the operating system
and architecture. In many cases, this results in a size mismatch
between pages and application-defined objects that can lead to
a significant loss in performance.
In this paper we describe the design and implementation of a
library that provides,
at the granularity of application-defined regions,
the same set of services that are commonly available at
a page-granularity using VM primitives.
Applications that employ the interface of this
library, called the Region Trap Library (RTL),
can create and use multiple objects
with different levels of protection
(i.e., invalid, read-only, or read-write)
that reside on the same virtual memory page
and trap only on read/write references to objects in an invalid
state or write references to objects in a read-only state.
All other references to these objects proceed at hardware speeds.
Benchmarks of an implementation on
five different OS/architecture combinations are presented
along with a case
study using
region trapping within a distributed shared memory (DSM)
system, to implement a region-based version of the lazy release
consistency (LRC) coherence protocol.
Together, the benchmark results and the DSM case study suggest
that region trapping mechanisms provide a feasible
region-granularity alternative for
application domains that commonly rely on page-based virtual memory primitives.
Modern operating systems typically
export to the user-level
the ability to manipulate the protection levels of virtual memory pages
and to handle traps to those pages from within an application.
Although originally intended
for user-level virtual memory management,
these mechanisms have
been used in many application domains
beyond those for which they were originally designed,
including distributed shared memory,
persistent stores, garbage collection and checkpointing.
Unfortunately, pages are often the wrong unit for data management,
since their size is fixed by the operating system
and architecture and this size usually has little in common with the
size of variable-length
data objects defined within an application.
When
multiple data objects with different access patterns occupy the same
virtual memory page,
a trap to one object on the page may adversely affect the state of any other
object on the same page.
Conversely, for data objects that cross page-boundaries,
traps must typically be handled one page at a time and may incur greater
overhead than necessary.
A variety of mechanisms have been proposed for
managing data at finer granularity or at a granularity defined
by the application.
There has been much research,
for example, on the
use of software checks, inserted by the compiler prior
to memory references, to determine the status of persistent
objects in a persistent store (e.g., White [26] and
Moss [18]).
Some systems
have also used software checks to implement
fine-grained sharing
or write collection
in a distributed shared memory (DSM) system
e.g., Shasta [22], Blizzard-S [23], and
Midway [6]).
Although the trade-offs between incurring a small software check
overhead on common
memory references versus
a large overhead on traps (which are much less common) have been
studied from an efficiency point of view
(Hosking and Moss [10],
Zekauskas et al. [28],
Thekkath and Levy [25]),
one of the advantages of VM trap
handling mechanisms seems to be their availability on most
modern operating systems and architectures.
Other object-based DSM systems
have
explored the use of program-level constructs to explicitly inform the
system when shared objects are referenced
(e.g., Orca [5], Amber [9],
Midway [6] and CRL [13]).
Although these systems avoid the need for both
software checks and traps,
they also impose
a more restrictive programming model on the user.
In this paper, we present the design of mechanisms
for providing, at the granularity of
application-defined regions of memory,
the same set of services
that are commonly available at a page-granularity
using virtual memory
primitives.
These mechanisms, implemented as a C library
called the Region Trap Library (RTL), use a
combination of pointer swizzling and
virtual memory protection to provide a
portable set of primitives
for manipulating protection levels to
regions and for handling
traps to regions from within an application domain
(and they do not depend on features of a particular
programming language).
Thus, for example, if three
regions A, B, and C use the RTL interface
and occupy
the same virtual memory page, and
A is in an invalid state,
B is in a read-only state,
and C is in a read-write state,
the RTL mechanisms will
generate a trap on a
read or write reference to A
or a write reference to B, but
allow read/write references to C
and read references to B to proceed
at hardware speeds.
The RTL mechanisms also allow an application domain to
map the same region at different protection
levels for different threads within the same address space,
and to determine both the set of regions
that have been modified since a previous
check and the set of modified addresses within those regions.
Together, these services form a superset of those
commonly offered by the operating system
through VM primitives at a page-granularity
and listed by Appel and Li in their paper discussing
the requirements
of application domains that make use of
VM primitives [4].
One of the main contributions of the mechanisms described in this
paper is that they are general purpose (i.e., they can be used
in different application domains and languages)
and they can be ported to many
different modern architectures and operating systems.
While earlier
papers have discussed the use of pointer swizzling for object
faulting [10][25],
to our knowledge pointer and register swizzling
have been implemented previously only within an
interpreted Smalltalk environment and specifically
for persistent storage [10].
Earlier systems have also not considered the problem of
providing more than one level of protection using these techniques,
or the problem of providing a solution that can work across different
architectures or in application domains other than persistent storage
and garbage collection.
We have currently implemented the RTL mechanisms on several
operating system/architecture combinations:
Solaris/MicroSparc, Solaris/UltraSparc, IRIX/R4400, AIX/PowerPC,
and LINUX/Pentium, and explored their use within a distributed
shared memory system.
We present some of the
issues involved in the design and implementation of these mechanisms
on different systems and
the overhead incurred by these mechanisms on each of these different
systems.
We also describe the implementation and use of these mechanisms
for a region-based version of the lazy release
consistency protocol within the TreadMarks DSM system.
In the DSM case study, we find that
the overhead estimates for region trapping
account for less than 1% of the parallel execution time
in five of the six applications examined, and 6% in the
other application.
The use of regions rather than pages for sharing data also leads
to significant improvements (up to 41%)
in performance for the applications used in this study.
An overview of this paper follows.
Section 2 presents some of the background and related work
for the ideas presented in this paper.
Section 3 describes
the design and implementation of the Region Trap Library.
Section 4 presents the results of some micro-benchmarks
that compare the overhead of
region trapping mechanisms to page-based VM primitives.
Section 5 presents
our case study using region trapping within a DSM environment.
In Section 6 we discuss the potential and
limitations of our approach and
present our conclusions in Section 7.
Our goal in this paper is to explore
the design and implementation
of mechanisms for modern architectures
and modern operating systems
that
offer the same set of services typically
provided through virtual memory primitives,
but at the granularity of
user-defined regions.
Appel and Li, in their paper on virtual memory (VM) primitives for user
applications, list the set of services commonly required
by applications that make use of these VM primitives
[4].
These services, generalized to include
region-based primitives in addition to VM primitives, are
shown in
Table 1.
These services are available in some form or another on
virtually all modern architectures but only at a page-granularity.
Some very early architectures (e.g., the Burroughs
6000 series of computers [16])
once provided non-page
granularity support for handling traps and managing data from user
applications, but such support is
not available on any modern architectures.
The mechanisms we propose use pointer swizzling for region trap
handling.
Pointer swizzling has been used previously in persistent object
and garbage collection systems.
In a persistent object system, pointers to objects
may have different representations when they reside on disk than when
they reside in memory,
and pointer swizzling is used to update the
values of pointers when objects are brought into memory or written
out to disk.
Most implementations use either
software checks to detect references to invalid objects
(see White [26] for a review)
or VM page trapping mechanisms
to fault objects into memory at a page-granularity
(e.g., Texas [24] and Objectstore [15]).
Table 1: Description of services typically required of applications using
page-based VM primitives, and analogous region-based RTL services.
Hosking and Moss [10]
implemented a technique called object faulting
within an interpreted Smalltalk environment.
In their strategy, pointers to
a persistent object
are swizzled to refer to a fault block that lies on a protected
page.
This fault block
acts as a stand in for the object when it is not in memory.
A reference to the object generates a trap,
and the object is faulted in to memory. In this scheme,
references to the object once it is brought into memory are indirect,
unless, as
suggested by Hosking and Moss, a garbage collection system
is used that can recognize these indirect references and convert
them to direct references.
Although this strategy provides some advantages over
persistent object systems that use page-granularity trapping mechanisms
or software checks prior to each memory reference,
its implementation is
language dependent and it makes extensive
use of virtual method invocation and built-in indirect references to
objects within an interpreted Smalltalk environment.
Thekkath et al. describe the use of unaligned access traps
for object faulting [25].
Unaligned access traps are generated by
some architectures on memory references to data that should
to be word aligned but is not.
This mechanism was used for fast synchronization in the
APRIL processor [2].
Using this approach for object faulting,
pointers to an object would be swizzled so
that they are unaligned, and a subsequent dereference to the pointer
would generate an unaligned access trap that could be handled by the
application.
However, this strategy, while providing a language
independent solution to object granularity trap handling,
cannot be used
on architectures that do not support
unaligned access traps (e.g., the PowerPC architecture),
and will only work in
limited cases on architectures that support
unaligned traps for some memory reference instructions but
byte level accesses for others (e.g.,
the SPARC architecture).
The mechanisms we describe in this paper are similar in some respects
to these latter two strategies, but are designed to provide greater
functionality
using mechanisms that do not depend on features of a particular
programming language,
and in an architecturally portable fashion.
Many
applications that use page-based virtual memory primitives
require the ability to trap on
read/write references to inaccessible pages
or on write references to read-only pages.
However, the use of unaligned access traps, as well the strategy
proposed by Hosking and Moss,
provide only the ability to trap on inaccessible objects.
One level of protection may be sufficient in the context
in which these earlier strategies have been proposed
(to fault objects into memory), but they do not suffice in
many other contexts. This includes checkpointing applications,
where the system has to be able to
detect write operations to objects that are either in a
read-only or invalid state,
or in the implementation of coherence
protocols within a distributed shared memory system, where
the system typically needs to be able to obtain updates to
an object on read references in an invalid state and to mark
changes to the object on write references in the invalid or
read-only state.
In this section, we describe the design and implementation of
the Region Trap Library (RTL). We begin by describing
the interface to the RTL.
Table 2: Example of how regions are defined in the RTL using both the C and
C++-style declaration of region pointers, and compared to the
analogous code using page-based virtual memory mechanisms.
Table 3: Skeletons of trap handler functions contrasting the way traps are handled
using virtual memory primitives and the region trapping mechanisms.
Applications that use the RTL must identify the areas of
memory that are to be managed as regions, the set of
pointers that are used to reference regions, and a handler
function
that will be invoked when a region trap occurs. A variety
of primitives are provided for specifying each.
To identify regions,
an application may use a memory allocator
called region_alloc(size) to both allocate and define
a region, or define a previously allocated range of memory as
a region using region_define(addr, size). An additional parameter
may be provided to these functions that
identifies a pointer that will be used to reference that
region.
A region pointer identified in this way is
referred to as a bounded region pointer, since it
can only be used to refer to the specified region.
Additional bounded pointers to the same region can be specified
using a primitive called region_bptr(&ptr1, &ptr2), which
indicates that ptr2 will be used to refer to the same region
as ptr1.
Unbounded region pointers, those that may refer to
any region, can be specified using a
primitive called region_ptr(&ptr). Region pointers can
be destroyed using a call to region_ptr_free(&ptr).
The region_ptr and region_ptr_free
calls are used to maintain
a list of pointers associated with each region.
Later, when protection levels are changed for a region
each of these pointers will be swizzled by the RTL
(see Section 3.2 for further details).
All calls to allocate or define regions,
or to modify protection levels,
update the region pointers that are declared by the user to
reference that particular region.
Region pointers can be used
in the same way as other C pointers including
the ability to use offsets within a region and to
manipulate pointers using pointer arithmetic.
The only restriction is that pointers not explicitly
identified to the RTL should not be used to reference regions
allocated or defined by the RTL.
The region handler function, potentially a different
one for each region, can be provided as an additional parameter
when the region is defined, or it may be specified
separately using a primitive called region_handler.
Region protection levels are set using a function called
region_protect. Protection levels are specified as they
are for the VM primitive mprotect, as PROT_NONE (to
trap on any subsequent reference to this region), PROT_READ (to trap only on
subsequent write references to this region), and PROT_READ|PROT_WRITE
(to enable all read or write references to this region).
These C functions present a low-level interface that is intended
to mimic corresponding page-based VM primitives whenever possible.
Table 2 shows how VM primitives (column 1) and
RTL primitives using this C interface (columns 2 and 3)
are used for handling traps, to virtual
memory pages in the former case and for regions in the latter case.
Table 3 shows the skeleton of analogous application trap
handler functions for both the VM and region trapping cases.
While the use of C as an interface permits this library to be
used in virtually any language environment,
the semantics of C are such that a programmer using this
interface directly would have to exercise some discipline in the way
regions and region pointers are defined and used.
For instance, there is no way in C to
indicate to the RTL when a pointer is declared that it will be
used to refer to regions, and to automatically inform the
RTL library that a pointer is no longer being used to refer to
regions when the scope within which it was declared has ended.
This necessitates the use of the routines
region_ptr (and region_ptr_free for pointers
that are not declared globally) when using
the C interface directly.
Within specific languages and application domains,
higher-level interfaces can be built that provide more elegant
ways to define regions, region pointers, and trap handlers.
In C++, for example, the template facility provides a means to simplify
the way in which region pointers are allocated and deallocated
from the RTL,
through a region pointer wrapper class as shown in column 4
of Table 2. Using C++ templates, the declaration of a region pointer
as region_ptr<type *> is sufficient both as a declaration
of the pointer and an indication to the RTL that this pointer will
be used to refer to regions.
Calls to the RTL functions region_ptr and region_ptr_free
are made automatically from within the constructor and destructor for this
pointer class. The access
operators for these wrapper classes are overloaded
so that references to a pointer declared in
this way are statically replaced by the compiler with direct
pointer references.
Figure 1: Setting region protection levels by swizzling region pointers between
three areas: invalid, read-only, and read-write. On architectures
with a large kernel address space (e.g., MIPS),
the invalid area is mapped to kernel space. On other architectures,
the invalid area is mapped to user space but does not occupy physical memory.
Within the RTL, three separate memory areas are maintained,
an invalid area, a read-only area,
and a read-write area.
The invalid area does not occupy any
physical memory and may in fact be outside of the
address space of the process
(e.g., in the kernel's address space).
The other two areas are
each composed of a set of virtual memory pages that
are mapped into the user address space.
In the read-only area,
all pages are mapped read-only,
and in the read-write area,
all pages are mapped read-write.
Space is allocated to a specific region
in each of these areas on demand and according to the protection
levels that are used for that region.
When region protection for a particular region is set to x
(where x is invalid, read-only,
or read-write), pointers to that region are swizzled so that they
refer to the copy of the region occupying pages in the area mapped
to protection level x.
This strategy is illustrated in
Figure 1.
If a region is currently in an
invalid state, pointers to that region point to an area within the
invalid space reserved for that region
(Figure 1(a)),
and a reference to that
region through any of these pointers will generate a trap.
If a region is currently in a read-only state,
pointers to that region refer to the copy of the region in the
read-only area
(Figure 1(b)),
and only write
references to that region will generate a trap.
Finally, if a region is in a
read/write state
(Figure 1(c)),
pointers to that region are swizzled to
point to a space reserved for that region in the read/write area,
so that all references to that region can proceed without a trap.
In this way, a lower
protection level for one region will
not result in unnecessary traps to another region occupying the same
set of virtual memory pages, since the pointers to each respective region
will simply point to different areas.
Mapping the same region
at two different protection levels within the same address space
can be done by declaring two different sets of pointers
to the same region but with different protection levels.
When a region trap occurs, the RTL goes through
the following sequence of steps:
- Determine the region to which the faulting address belongs,
the region pointer(s) that refer to this region,
and the application's trap handler for that region.
- If the protection level is being changed within the
region trap handler,
decode the faulting instruction and then
swizzle both the register containing the faulting address and
pointer(s) in memory referring to the faulting region.
Recall that the pointers referring to each region have
been identified using region_ptr or
region_bptr calls.
Our prototype implementation of
the RTL uses a binary
search to locate region addresses stored within an AVL tree.
Although faster implementations of region lookup are possible,
this approach provides
adequate lookup times for the applications on which we have
conducted experiments.
Once the region is located,
the trap handler specified by the application
for that region is invoked.
Region pointers bound to this region and the address of the application's
handler function for this region are stored within the nodes of
this tree and thus require no additional effort to locate. Unbounded
region pointers, if any have been declared, must be searched separately
to see if any refer to this region.
It is the responsibility of the application's trap handler to
determine how to handle a region trap and to indicate to the RTL
what state
the region should be mapped to
prior to returning from the handler (as in Table 3).
When region_protect is invoked from the application's handler,
the register and all pointers known to be referring to the region
(as specified as parameters to
region_alloc,
region_define,
region_ptr, or
region_bptr)
are swizzled.
Swizzling the register containing the faulting address requires
first decoding the instruction that generated the fault in order
to determine which register requires swizzling, and then
modifying that register.
Region pointers may point
to any address within a region. Consequently,
when pointers or registers are swizzled from one memory
area to another,
their offset from the start of the region in those respective
areas must be preserved
(this is what permits offsets and pointer arithmetic to be used).
A key concern with the efficiency of this strategy arises from the
fact that some transitions to the read-only state for a region
require updating the read-only copy of the region,
in order to maintain consistency.
In particular, on transitions directly from the read-write state
to the read-only state, or transitions from the read-write
state to the invalid state and then to the read-only state,
this update must be performed.
Further, the
pages occupied by the read-only copy of the region are
themselves in a read-only state, and they must first be
unprotected (using mprotect)
prior to beginning the update, and then re-protected
once the update is complete.
The performance implications of this read-only copy update are
considered in the benchmarks of Section 4. Regions that transition only between
read/write and invalid states
or read-only and invalid states
do not incur this overhead.
The allocation of the region in two areas of memory,
a read-only area and a read-write area,
facilitates
an additional service that many applications can make use of
which is often
referred to as a diff.
Using this service,
an application may, at any point during execution, query the
RTL to determine the set of memory locations in a region that
have been modified
since a previous write trap or checkpoint operation.
Many distributed shared memory systems and checkpointing applications,
for example, implement such a service at a page-granularity.
The region-based distributed shared memory implementation within
Treadmarks, described in
Section 5 also exploits this
service, replacing Treadmarks' existing page-based diff mechanisms with region-based diff mechanisms.
The RTL has currently been implemented on the MicroSparc and
UltraSparc architectures, both running Solaris, the SGI MIPS
R4400 architecture running IRIX, the IBM RS/6000 architecture
running AIX, and the Pentium architecture running LINUX.
Some of the issues involved in implementing these strategies
on various architectures, and in particular, some of the requirements
from the operating system, architecture, and compiler for an
implementation of region trap handling on these and other platforms
are discussed in this subsection.
Setting region protection levels to invalid requires the ability
to swizzle
pointers to an area that is guaranteed to generate a trap.
The MIPS architecture, one of the four architectures on which we have
currently implemented the RTL, makes this particularly easy. On the MIPS,
addresses with the high order bit set refer to kernel space addresses,
and the region trapping implementation can take advantage of this by
swizzling this high order bit on
pointers to regions in an invalid state.
On the other architectures,
our implementation creates
an additional area within a processes' address space that is mapped
as inaccessible
and never occupies physical memory. Invalid regions are mapped to this
area. These two approaches for mapping the invalid area behave
the same and use the same amount of physical memory,
but the latter solution potentially occupies
three areas in the virtual memory address space of a process for
each region.
The use of precise interrupts on protection violations
by the architecture is an important
prerequisite for the implementation of region trap handling.
In the absence of precise interrupts, the trap handler would have
a more difficult time determining which instruction/register caused
the fault, and what machine state may have been altered.
Fortunately, most modern architectures (including all of the
architectures discussed in this paper)
use precise interrupts
on protection violations.
The requirements from the operating system for an implementation
of region trapping are relatively few.
When a trap occurs and the RTL's trap handler is called,
the operating system must provide enough processor context to
the RTL trap handler
to allow it to determine the faulting address,
the faulting instruction, and the register that
contains the faulting address. Additionally, trap recovery in the
RTL requires the ability to modify and restore execution context.
The versions of UNIX on which we have currently implemented the
RTL (IRIX, AIX, LINUX, and Solaris) all provide this level of
support.
There is some concern that the compiler might cache region
pointers in registers and that these registers,
which are not known to the RTL will not be swizzled
upon subsequent changes in protection levels.
As a result later references to the region using the cached
register value will not generate the proper behaviour
(either generating unwanted traps or not generating desired traps).
Since protection levels are changed by calling the
function region_protect and since the compiler
should not cache values that can be changed inside of the
function call across such calls,
the compiler should not create these potentially
dangerous register caches.
The problem is exacerbated because
protection levels might be changed by a function that is called
asynchronously (e.g., as a result of a trap).
In the benchmarks that we have run on the five different platforms,
as well as in the distributed shared memory experiments we have
conducted using the RTL in the SGI MIPS environment,
we have not
encountered any instances of this type of pointer aliasing.
It is conceivable that some
compilers may perform such aliasing within registers.
Fortunately, if such a problem were to arise,
by declaring region pointers as volatile, the compiler is forced
to generate code that reloads a region pointer
(albeit probably from the cache) each time it is
dereferenced, and the
compiler is then not able
to create register aliases to regions.
This solution is clearly more
restrictive than necessary, and will result in some
performance degradation.
Ideally, compilers
should also support a flag that prohibits the aliasing of pointers
in registers
without requiring these pointers to
be declared as volatile.
In this section, we present the results of benchmarks that
measure the overhead of region
trapping mechanisms relative to standard VM page trapping
primitives.
These benchmarks are not designed to provide insight into
overall
application performance using page or region-based trapping
mechanisms, since the two techniques will likely result in
a different number of traps being generated.
Instead, these benchmarks provide some indication of how
well different architectures and operating systems
support region trapping mechanisms
and
whether the overheads incurred by the
region trapping
mechanisms would be prohibitive for
application domains that
commonly make use of VM primitives.
Section 4.1 describes the benchmarks that we use and
Section 4.2 discusses the results of these benchmarks.
Table 4: Times (in microseconds) comparing VM primitives,
RT-basic and RT-update.
RT-basic refers to region traps on which the read-only copy of the region
does not need to be updated, while RT-update refers to
region traps on which the
read-only copy of the region must be updated.
RT region size is equal to the system page size.
Numbers on the 2nd line for each system are the ratio of RT test costs
relative to the corresponding VM test.
Times reported are the average of multiple iterations of each test on
different pages or regions.
Three benchmarks are used.
The first, referred to as trap,
measures the overhead of using trap mechanisms.
For VM primitives, this
is simply the cost of
entering and exiting a signal handler.
For RT primitives,
the trap time also includes
the additional cost (within the signal handler)
of decoding the instruction,
locating the region,
calling a null application trap handler,
and swizzling the
region pointer and a register.
Appel and Li observe in their paper that applications that
use virtual memory primitives typically perform one of the following
two sequence of operations:
-
Prot1:
protect one page and, on a
subsequent trap to that page, unprotect the page from inside the trap
handler, or
-
ProtN:
protect a set of N pages and,
on a trap to any of these protected pages, unprotect the page
that caused the trap from inside a trap handler.
A comparison of these
two sequences provides a
better understanding of the relative overheads involved in using trapping
mechanisms than simply measuring trap costs alone.
Consequently, we use two benchmarks
that are patterned after these two sequences.
These two benchmarks, referred to as Prot1 and ProtN,
are constructed in the same way as described
in the Appel and Li paper.
In the Prot1 test, a protected page or
region is referenced and, inside the trap handler, the page or region is
unprotected and another one is protected.
In the ProtN test,
100 pages or regions are protected, and each one is referenced and
unprotected one at a time within a trap handler.
A large number of repetitions
of these sequences are conducted
in order to obtain
an average cost per sequence
(typically 10,000 to 100,000 repetitions were used,
depending on the time taken to execute each sequence).
However, because of the caching effects
that occur as a result of doing multiple repetitions,
all results should be considered optimistic.
Additionally, the results
do not consider overheads the RTL would incur as a result of
swizzling multiple pointers
(since the number of such pointers will typically
be small and the overhead required to
simply modify a pointer will be negligible)
and the design of the trap benchmark
does not consider overheads incurred to search for the
faulting region.
However, since the Prot1 and ProtN benchmarks
use 100 regions,
the costs to find the appropriate region are included in those
benchmarks.
Although the time required to find the appropriate region
in the RTL depends on the number of regions,
similar overheads
would be incurred using VM primitives if the action
taken on a trap depends on the object generating the trap.
For all three benchmarks (trap, Prot1, and ProtN),
region trap overheads are classified as
RT-basic and RT-update.
RT-basic measures the cost of region traps
that do not require an update of the
read-only copy of the region,
while RT-update measures the cost of region traps that
do require such an update.
Region size plays a significant role in the cost of RT-update
traps, but no role in the cost of RT-basic traps.
The first set of tests use a region size that is equivalent to the
size of a page on each system
(8 KB on Solaris and 4 KB on the others).
Subsequent tests show the effect of varying the region
size on the Prot1 benchmark.
Table 5: Prot1 benchmarks for varying region size.
K is the number of pages
occupied by a region. All times shown are in microseconds.
Times reported for RT-update are the average of
multiple iterations of the Prot1 test on the same region.
Table 4 shows the results of the three tests on each
of the systems on which our RTL prototype has been implemented.
For each OS/architecture shown in this table,
the second line shows the ratio of the cost of the RT benchmark
relative to the equivalent VM benchmark.
Thus, for example,
RT-basic trap time under IRIX is 96 microseconds,
while the VM trap
time is 65 microseconds,
resulting in a relative cost ratio of 1.5. A number
less than 1 implies that the RT benchmark is faster than the
equivalent VM benchmark.
Entering and exiting a signal handler requires crossing OS protection
boundaries. This is fairly expensive on all architectures
that we study, though the fast exception handling technique
described by Thekkath and Levy [25]
would significantly reduce this cost
for both VM and RT primitives.
Protection trap times on the LINUX/Pentium configuration
are particularly low when compared with the
other OS/architecture configurations,
with trap times five times lower ( )
than the next best time
( on the AIX system).
RT-basic trap costs are between
1.2 and 1.5 times more expensive than VM trap costs on all architectures
except LINUX (due to its fast protection traps and more complex instruction
set), where RT trap costs are 1.9 times more expensive.
RT-update trap costs, as would be expected, are significantly higher,
ranging from 3.1 times more expensive than VM trap costs
on the AIX system to 9.6 times more expensive on LINUX.
However,
in our measurements of the components of this overhead,
we found that
for regions equivalent to or smaller than the size of a page,
the cost of the memcpy function
used to copy regions from the read-write area to the read-only
area makes up only a small portion of this cost.
Most of the
additional cost for RT-update comes from the fact that the
pages occupied by the read-only copy must be unprotected using
mprotect before the update can begin, and then reprotected (again
using mprotect) after the update has completed.
mprotect, a system call that requires crossing
OS protection boundaries and shooting down TLB entries,
is relatively expensive on all
of the platforms we have used in conducting our experiments.
The Prot1 and ProtN benchmarks reveal a very different picture
than trap overheads alone.
For the VM case, protection levels are
set using mprotect.
A region_protect in RT-basic is very cheap
by comparison
(typically less than ), since it does not require any
system calls.
As a result,
RT-basic Prot1 times are smaller than VM Prot1
times across all architectures, with differences ranging from
a factor of 0.5
to 0.8.
Prot1 and ProtN times are almost identical for
RT-basic, due to the small overhead of a region_protect call.
For the VM ProtN test,
protecting multiple pages in one call to mprotect is
cheaper than protecting each page one at a time, so
VM ProtN times are less than Prot1 times.
However, RT-basic
ProtN times are still lower than VM ProtN times,
by factors of 0.6 to 0.9.
RT-update Prot1\
times are significantly higher
than RT-basic Prot1 times, as would be expected.
In RT-update however,
since a
significant proportion of the cost is due to using
mprotect twice
to unprotect and reprotect the page
occupied by the region, and the VM Prot1 test performs the same number of
mprotect calls,
RT-update Prot1 times range from being just 2.4 times
higher than VM Prot1 on IRIX to 5.1 times higher on LINUX.
RT-update ProtN times range from being 4.3 to 5.8 times
higher than VM ProtN times.
In this subsection, we consider the effects of defining large
regions that span multiple pages. Since some region traps
require copying the region from one area to another,
it stands to reason that region trapping overheads in these cases
will increase significantly as the region size is increased, although
the cost of using mprotect within a region_protect call
in such cases will be amortized over the larger regions.
The cost of handling traps to large regions is considered
from two perspectives: (1) relative to the cost of handling a
trap to a region for which the size is equivalent to one page,
and (2) relative to the cost of handling a trap to a
page-based strategy that would handle traps to the same
number of pages as spanned by the region.
For page-based strategies, the premise for the
Appel and Li benchmarks is that typical applications incur a fault
on each page separately regardless of how large the object is,
since such strategies do not usually take application characteristics
into account. Consequently, if a region spans K
virtual memory pages in a region-based approach,
the analogous page-based applications using VM mechanisms
will likely incur K traps for every one trap incurred by the region-based
approach.
Table 5 shows the results of the Prot1 benchmark
for region sizes equivalent to one 1 page, 64 KB and 256 KB.
RT-basic times, which are not affected by region size,
are not shown.
Although experiments in the previous subsection were
performed using multiple iterations of the same test across one
hundred regions, this was not possible for the experiments here because
of the large region sizes involved
(declaring one hundred such regions results
in paging on some of these machines).
These tests are conducted
using multiple iterations on the same region, and are thus
more prone to caching effects
than the experiments in the previous subsection.
For comparison to the region trapping version,
VM times show the cost of K Prot1 sequences when
the region spans K pages.
For 64 KB regions, although memcpy
costs go up significantly, RT-update Prot1 times increase
by relatively small factors in the range of 1.6 (on the UltraSparc) to
3.5 (on the MicroSparc), when compared to the times
for region sizes equivalent to the page size.
RT-update times for the Prot1 benchmark are
lower than K Prot1 sequences in the VM case
for four of the systems studied (ranging from 0.4 to 0.9),
and somewhat higher on the other
(1.4 on the Solaris/MicroSparc system).
This difference is reduced on some
architectures and increased on others for 256 KB regions,
so that the
costs of RT-update relative to K VM Prot1
tests range from 0.3 to 1.0.
However, these latter comparisons
assume for the VM case that every page spanned by the region
would be referenced and that the VM strategy does not
employ any strategy to increase the effective page size.
A worst case comparison for the region trapping case would
be in instances where only
one of the K pages spanned by the region is actually referenced.
In such cases, RT-basic costs, which are unaffected by region size,
are the same relative to the VM case.
However, RT-update costs would look significantly worse, by
factors of 7 to 11 for 64 KB regions,
when compared to a VM based strategy that
handles a trap only to the page that was referenced.
The benchmark results of this section provide some insight into the
overheads involved in the use of the region trapping mechanisms
described in this paper.
The architectures on which region trapping mechanisms
were implemented and
studied
vary significantly in speed and in the complexity of the
instruction sets. Operating system overheads also play a
significant role in these costs.
Overall, despite the seemingly high overhead of keeping the
read-only copy up-to-date
with respect to the read-write copy,
region trapping overheads
are competitive with VM overheads.
For instance, for regions equal to the size of
a page, the Prot1 benchmarks show region trapping to be faster
by factors of 0.5 to 0.8
for transitions on which the read-only copy is not updated,
and slower by factors of 2.4 to 5.1 when the read-only copy does need
to be updated.
For much larger regions, RTL costs in the Prot1 benchmark
are typically comparable to or lower than VM costs
when K traps to a page in the VM case are considered equivalent
to one trap in the RTL case for regions spanning K pages.
Since these benchmarks provide
only a microscopic view of RTL and VM overheads, the question of
how real applications will perform using these mechanisms cannot
be answered without examining the applications themselves.
In particular, the number of traps that are actually generated
is entirely application dependent and is likely to be
different within a page-based and region-based version of the
same application. For instance, when multiple objects
occupy a single page, a page-based strategy may generate
more traps than a region-based strategy (as a result of
false sharing for example), or fewer
(if all of the objects on that page are
accessed together). Conversely,
if an object is much larger than a page, a page-based
strategy may generate more traps than a region-based strategy
if it faults on each page of the object separately, or an
equivalent and perhaps fewer number of traps if not all of
the pages occupied by an object are typically referenced at one time.
To obtain a clearer picture of how RTL mechanisms would behave
within a real application domain, we implemented a region
trapping based
coherence protocol within a distributed shared memory system.
This is described in the next section.
This section presents some results from a case study which uses region
trapping within the TreadMarks distributed shared memory (DSM) system.
TreadMarks uses page-based VM primitives to implement an efficient
coherence protocol called lazy release consistency (LRC),
described in detail by Keleher et al. [14]. We have
modified TreadMarks to support a region-based version of LRC that uses
region trapping to handle traps and manage data at the granularity of
regions rather than pages.
For comparison,
we have designed and implemented another coherence protocol,
called Multiple-Writer Entry Consistency (or MEC) which is described
in detail in an earlier publication [20].
This protocol
is similar to entry consistency [6]
from the programming perspective except
that it uses program-level annotations that are non-synchronizing.
In this paper
versions of the applications
that have been implemented using this protocol are
referred to as the Annotated Regions (AN) versions.
They
behave like the region trapping versions except that they use
program-level annotations rather than traps to indicate when
regions are referenced for read or write.
While the annotated (AN) versions are
significantly more difficult to program,
a comparison between the region trapping and annotated regions versions
of these applications highlights the overhead of the region trapping
mechanisms. At the same time,
a comparison between the page-based version and
region-trapping versions highlights both the cost of using region
trapping versus VM mechanisms as well as the trade-offs between using
regions rather than pages for data management.
Table 6: Snapshots of some code within SOR using VM, RT, and AN.
M is the number of rows and NS is the size of each row.
Six applications were used in this study:
matrix multiplication (MM),
red-black successive over-relaxation (SOR),
blocked contiguous LU-decomposition (LU),
a Floyd-Warshall algorithm for finding shortest
paths in a directed graph (FLOYD),
integer sort (IS),
and the traveling salesperson problem (TSP).
TSP, SOR, and IS are all from the
suite of applications used in earlier
TreadMarks studies [1],
LU is from the Splash-2 benchmark suite [27],
and MM and FLOYD were written locally.
Table 6 contrasts how one of the applications used in our study, SOR,
is written to use each of the three protocols that we compare,
page-based LRC (VM), region trapping LRC (RT), and annotated regions
LRC (AN). Only a portion of SOR is shown but the example illustrates
the program-level differences between these three approaches. In the
original TreadMarks system, shared data must be allocated dynamically
using the Tmk_malloc routine. In the original VM version of
SOR (obtained with the TreadMarks distribution), each row of the two
matrices (called red and black) is allocated separately
using Tmk_malloc. In the RT version, each row is defined as a
region by changing the Tmk_malloc call to
region_alloc and providing a pointer to that region as a parameter.
The rest of the code is identical for both page-based and
region trapping versions of SOR.
In the annotated regions version, each region is explicitly associated
with a region identifier for that region (redX and blackX
in the example),
that is used in subsequent readaccess or
writeaccess calls
to identify a series of references to the region.
Obviously a key motivation for implementing the RTL is
to avoid having to annotate programs as shown in the AN example.
The other five applications required similar modifications to
implement region trapping and annotated versions, although some
of these applications use aliases to region pointers
that also need to be declared as region pointers.
In MM, all of the rows in
a matrix used by a single processor are aggregated into
a single region.
In FLOYD, each row of the
shared matrix is defined as a single shared region.
In LU, each block is laid out contiguously and allocated separately
in the original Splash-2 version.
These blocks are allocated as regions in the RT version.
In IS, there is a single shared data structure, a shared bucket,
which is defined as a region.
Finally,
the original TreadMarks version of TSP allocates a single block of shared
data using a single Tmk_malloc call.
This block contains several different data structures.
The RT version separates some of these data structures into
separate regions, the largest of which is still about 700 KB in size.
We have conducted a series of experiments
on a cluster of four 175 MHz R4400 SGI workstations
connected by 155 Mbps links to a
Fore Systems ASX-200 ATM switch.
Table 7 shows the problem sizes used in these experiments,
the size and number of regions
defined in the region trap and
annotated region-based versions
(only the main regions are described),
and the execution times of the applications on
one processor and on
four processors for each of the three models.
Table 8 shows the number of traps that occur on a typical
processor in the RT and VM versions of the applications,
the RT overhead as a percentage of the runtime,
and the number of messages and bytes
transmitted between processors
(relative to one processor)
for both the RT and VM versions.
Table 7: Applications used in DSM study and the corresponding problem size
descriptions and execution times (in seconds) on one processor
and under VM, RT and AN on four processors.
Table 8: Total number of traps generated, and messages and kilobytes transferred
for RT and VM and the estimated RT overhead as a percentage of
parallel execution time.
Region trapping overheads are estimated by multiplying
the number of traps incurred of each type
by the cost measured for that type of trap
on the appropriate architecture (as shown in Table 4).
These overheads account for
less than 1% of the parallel execution time
in five of the six applications,
and 6% in the other application (TSP).
Those overheads that
do exist arise largely from the cost of updating the
read-only copy of the region (when required) on transitions to
the read-only state for a region.
In TSP, this overhead is incurred within a critical section and
has rippling effects on other processors waiting to enter that critical
section, thereby causing a still larger difference in overall
performance between the two region-based protocols (15%).
The negligible difference in performance
between the
region trapping and annotated regions versions in all but one of
these applications
(TSP) suggests that region trapping costs play a minimal role
in most cases.
and that
the significant difference in the performance between
these region trapping applications and those based on VM primitives
results from the differences in managing data at a
region rather than page-granularity.
These results demonstrate that the RTL can be used to eliminate
the need for programmer annotations in such programs while
maintaining efficient execution.
Compared to the VM version,
the two region-based protocols improve performance in these
applications by significant margins ranging from
18% in TSP to 41% in SOR on this platform.
Using application-defined regions as the medium for sharing data
reduces the number of traps that occur and the number of messages
communicated in all six applications.
Interestingly, however, the number of bytes
communicated between processors is significantly
higher in the region-based
protocols in two of the applications, LU and TSP.
While a better choice of regions might improve this situation,
the increase in bytes using regions in these two applications is a
result of defining large regions that span multiple virtual memory pages.
These applications suffer from false sharing
within regions, where modifications to the entire region
are transmitted between processors on a trap even though much of region
may not be used by the other processor.
On the SGI platform,
the reduction in the number of
messages communicated between processors in these two applications
compensates for the increase in the number of bytes transmitted.
It is worth noting that in our environment
the RT and AN versions of MM execute significantly
faster than the VM version.
This is rather surprising, since other studies
report near-linear speedup for page-based DSM implementations of MM.
We do not obtain near-linear speedup for the VM version of MM
because we use a matrix size that results in false sharing,
our execution times include the time required to fault all data
to remote machines,
and IRIX 6.2 appears to delay the
delivery of SIGIO signals to an executing process until it
either blocks or its quantum expires.
In some cases,
this results in delays when requesting remote pages
or regions.
While such delays are not present in other environments
we've used in previous studies
we have found that the AN version of MM
still outperforms the VM version
(although in this case,
the execution time is only improved by 12%)
[20].
This earlier publication [20] also provides a
more detailed discussion comparing
the performance of page-based (VM) and region-based protocols (AN).
These results provide some evidence that
the overhead of the region trapping mechanisms within a DSM
environment
are reasonable.
Since trapping overheads account for a small proportion
of the execution time for both RT and VM mechanisms, the key
factor in determining whether region trapping is useful within
the distributed shared memory context lies in the trade-offs
between using regions rather than pages for managing shared
data, both from a programming and performance perspective.
Studies by Adve et al. [1]
and by Buck and Keleher [7]
compare the performance of page-based LRC
to object-based EC. Each study suggests
that page-based systems are competitive with
and sometimes better than object-based systems, while a
similar study by Neves et al. [19] has found object-based
systems to be much better.
However, unlike the page and region-based versions of LRC
used in the study presented in this section,
page-based LRC and
object-based EC
differ not only in the use of pages rather
than objects (regions)
as the granularity of data management, but also
in terms of the synchronization model (release consistency
versus entry consistency)
and coherence protocols (lazy release consistency versus
write-update) that are used. Consequently, the results
of those studies are not directly comparable to those presented
in this section.
The comparison between the page and region-based versions of LRC
presented in this section suggest that many applications may benefit
from using these region trapping mechanisms instead of the traditional
page-based VM mechanisms. However, a detailed examination of these
trade-offs between pages and regions within a distributed shared
memory system are beyond the scope of the study presented in this
section. Consequently, a number of factors that
may also influence
the choice of whether to use pages or regions for managing shared
data
have not been considered here.
This includes
the use of page aggregation techniques, which increase the effective
size of a page [3] and would likely improve the
performance of the VM case for some of the coarse-grained applications
used in this study, and the use of
other coherence protocols such as scope
consistency [12], which captures some of the advantages of
object-based protocols such as entry consistency.
The benchmarks and case study of
Sections 4 and 5 highlight both the
potential and the limitations of the current RTL implementation.
The primary limitations, both in terms of the programming interface and
performance, can, as it turns out, be easily addressed.
In this section, we briefly discuss these limitations and
how they can be
overcome in the RTL.
One of the key performance costs in the RTL, the need to
update the read-only copy of the RTL, can be eliminated by mapping
the read-only and read-write memory areas to the same
physical memory area.
Once this is done, all of the RT-update costs
described in Section 3.3
and shown in the figures of
Section 4 are eliminated since
only a single physical copy of the region needs to be maintained
(unless a copy is required in order to compute diffs).
This also eliminates the additional physical memory overhead
incurred by the current RTL implementation.
The other major concern is with the RTL interface itself, which
requires all pointers to a region to be explicitly declared.
In work conducted concurrently and independently of our own,
Itzkovitz and Schuster [11]
present an alternative approach that provides the functionality that
the RTL implements but without having to manipulate pointers to those regions.
Itzkovitz and Schuster's MultiView system allocates each region
on a separate virtual memory page, but maps each of those regions
to the same set of physical memory pages.
This allows the
virtual memory protection levels of each region to be manipulated
independently while still allocating different regions on the same
page.
The MultiView approach presents a simpler
programming paradigm than the RTL
(regions must still be identified,
but pointers to regions do not).
However, MultiView may also
consume a significant portion of the virtual address space
because a single virtual memory page must be allocated for
each region,
even if the region is only a few bytes in size.
This leads to a potentially more serious performance
drawback in that
each virtual memory page requires a single TLB entry.
Since most current architectures have relatively limited TLB sizes,
applications that reference many small regions may
generate significantly more TLB misses using the MultiView approach.
In contrast the
RTL approach has a small
fixed virtual memory and TLB entry overhead that is
dependent only on the total size of the virtual memory consumed
by the application.
Further, once the RT-update costs in the RTL have
been eliminated using the technique noted above,
changing RTL protection
levels will be a fraction of the cost of manipulating virtual
memory protection levels.
These latter costs, using the expensive
mprotect system call,
are required both in traditional page-based
approaches and by MultiView.
Thus while the MultiView approach offers clear advantages
as far as the programming interface is concerned
these performance issues
may make the RTL approach more suitable for very
fine-grained sharing.
In this paper, we have described the design and implementation of
the Region Trap Library,
which provides the same functionality, at the granularity of
user-defined regions, that application domains typically require from
virtual memory primitives at a page-granularity.
One of the main contributions of the mechanisms used in
this library is
that they
do not depend on features of a particular
programming language
and they are portable
across several architectures.
Benchmarks on several operating systems and architectures
suggests that the overhead of these mechanisms is
typically competitive with their page-based
counterparts.
Our implementation of a region-based version of the lazy
release consistency coherence protocol within the TreadMarks
page-based DSM system
demonstrates the applicability of region trapping mechanisms
within some of the domains that make use of virtual memory
primitives.
In the DSM context, we found region trapping
overheads to be typically less than 1%, with the exception of one
application that incurred an overhead of 6%.
Together, the benchmark results and the DSM case study suggest
that the region trapping mechanisms implemented in the
Region Trap Library
provide a feasible
region-granularity data management alternative to VM primitives
within some of
the application domains that commonly rely on page-based VM
primitives.
Further study is needed to
identify the overhead of the region trapping mechanisms
within some of these other application domains,
and to determine the value of using regions
rather than pages as the unit of data management in these
domains.
The authors gratefully acknowledge the financial support
of the Natural Sciences and Engineering Research Council of Canada
(NSERC).
We thank Graham Smith for porting the RTL to LINUX on the Pentium Pro
and Diego Moscoso for discussions during the early stages of this work.
We thank Ken Sevcik and the POW group at the University of Toronto for
providing us with access to their IBM systems.
Finally we wish to thank
the anonymous referees for their careful reading
of the paper and for their insightful comments.
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